Airport forecasting

By :
Mohammed Salem Awadh
Consultant
Airport
Forecasting
Collection Articles
Part One

Contents :
Introduction ----------------------------------------------------
1- Airport Performance -----------------------------------
2- Hard Target ---------------------------------------------
3- Forecasting by Objective -----------------------------
4- Getting The Right Picture -----------------------------
5- Short Term vs Long Term Forecast----------------
6- Measuring Forecasting Accuracy ------------------
7- Airport Forecasting ------------------------------------

Introduction:
Long time ago, a group of students assigned to carry
forecasting project by using ARIMA model, at that time I
have a good contact with faculty of Engineering at Aden
University, as a field supervisor and I asked them to
utilize and forecast the data of Air Yemen. The work is
fair and good, we are presented the work in Warangal
conference - India.. the following link shows this work.
http://www.slideshare.net/wings_of_wisdom/a-
multiplicative-time-series-model

Today – the forecasting concept is enhanced by many
practical procedures, advance tools
and packages of software, and many
companies practice these techniques.
A new concept is used by using
Max/Min Signal Tracking
Approach, which define two
main elements that derive the
Forecasting Model i.e
Displacement and Rotational
so accordingly we can setup a
forecasting accuracy matrix
that positioning the
parameters of the
model in the main
quartets locations
according the preset
constrains for R and
Signal Tracking as
shown in figure.
While addressing
Airport Forecasting, it
is the factor for
Airport Capacity Planning, either to set the right
infrastructure or planning ahead to avoids a congestion
issues, and defining the right seasonality patterns for the

purpose of assigning the right size of labor force,
especially in a peak time.
But, defining the KPIs system is the main issue for
airports performance, by setting the targets and their
level of acceptance. ( short and long terms). ■

“Excellence is never an
accident. It is always the
result of high intention,
sincere effort, and
intelligent execution; it
represents the wise choice
of many alternatives
– choice, not chance,
determines your destiny.”
Aristotle
26
Any performance report always reflect the comparison
between the existing period vs the same period of the
previous year giving an indicator of how the airline perform in
the past, but in a planning process that involving forecasting
the story is different, we compare what is achieved to what is
planned (forecast) by using present figure vs.
future (forecasted) figures, to indicate what is the best
approach, we to evaluate the standard error for both scenario.
Toronto International Airport Case Study:
1- Input Data:
The data is split in two parts – Basic Data and Evaluation
Data:
Basic Data: Monthly 3 years data period (2010-2012)
Evaluation Data: 6 months of 2013.
2- Signal Tracking Analysis:
The max/min signal tracking approach define three points are
out of the range data are 9, 21, and 35. Reporting by ± 4.77
as shown in the graph.
3- Seasonality Model:
Coefficient of Determination: 99.1% and Max/Min Signal
Tracking: ± 4.77
4- Results:
Passengers Forecast 2013= 36,705,584 Growth= 5.50
Past Vs Future:
By calculating the standard error for both scenario (classical
one and the forecasted one).
The result fairly support the forecasted approach by Standard
Error of 0.53 represent by Future period, while Standard Error
of the classical approach is 3.11 represent by past period.
Prepared by: Mohammed Salem Awad
Research Scholar – Aviation Management
Airport Performance – Past vs. Future, It is your choice!
Airports Forecasting
New Method Passenger Movements 2013
Month Forecast (F) Actual (A) (F) - (A) / (F)
Jan 2,886,017 2,781,425 (3.62)
Feb 2,707,698 2,565,532 (5.25)
Mar 3,094,788 3,074,281 (0.66)
Apr 2,952,835 2,881,764 (2.41)
May 3,012,450 2,996,758 (0.52)
Jun 3,143,234 3,093,930 (1.57)
Jul 3,583,257
Aug 3,672,747
Sep 3,061,353
Oct 2,977,543
Nov 2,633,804
Dec 2,979,858
Standard Error 0.53
Toronto International Airport
Classic Method Toronto Airport
Month 2011 (11) 2012 (12) (12) - (11) / (11)
Jan 2,627,686 2,682,581 2.09
Feb 2,438,279 2,764,028 13.36
Mar 2,826,974 2,621,169 7.28-
Apr 2,684,556 2,951,030 9.93
May 2,783,106 2,825,987 1.54
Jun 2,865,070 2,832,779 1.13-
Jul 2,292,149 2,972,845 9.70-
Aug 2,357,974 3,351,065 0.21-
Sep 2,806,234 3,523,644 25.56
Oct 2,683,757 2,908,905 8.39
Nov 2,386,911 2,827,934 18.48
Dec 2,682,581 2,528,817 5.73-
Standard Error 3.11
1700000
2200000
2700000
3200000
3700000
4200000
NoofPassengers
TIME (Month)
Toronto International Airport
Forecast
Total Passengers 2013
Actual
R
2
= 99.1 %
S.T.= 4.77 (2010 - 2012)
2013 (F) = 36,705,584 Pax
Growth = 5.50
3.11 Past 0.53Future
CAMA Magazine | issue 20 | June, 2014

camamagazine.com
27Airport Forecasting
Canadian Airports: Forecast of 2013
Airports Forecasting 2013
Deerlake Regional Airport 334,371
Fort McMurray Airport 1,026,957
Kelowna International Airport 1,455,559
Victoria International Airport 1,510,075
Winnipig International Airport 3,638,834
Halifax International Airport 3,725,705
Ottawa Macdonald-Cartier Int. Airport 4,878,335
EIA International Airport 6,881,180
Calgary International Airport 13,963,704
Montreal International Airport 14,538,536
Vancouver International Airport 17,945,517
Toronto Person International Airport 36,705,584
YVR Airport
Jan 1,382,910 1,349,201 (2.44)
Feb 1,296,412 1,270,257 (2.02)
Mar 1,474,340 1,429,669 (3.03)
Apr 1,402,801 1,364,586 (2.72)
May 1,509,221 1,481,471 (1.84)
Jun 1,594,422 1,611,297 1.06
Jul 1,783,904
Aug 1,838,650
Sep 1,525,463
Oct 1,412,963
Nov 1,261,172
Dec 1,463,258
Total Forecast 17,945,517 Standard Error 0.61
EIA Airport
Jan 545,231 551,651 1.18
Feb 537,556 541,616 0.76
Mar 594,140 594,879 0.12
Apr 573,410 572,370 (0.18)
May 567,688 573,654 1.05
Jun 561,298 557,077 (0.75)
Jul 619,912
Aug 639,047
Sep 548,559
Oct 558,790
Nov 547,037
Dec 588,512
Montreal Airport
Jan 1,189,631 1,134,558 (4.63)
Feb 1,121,519 1,072,426 (4.38)
Mar 1,287,320 1,284,637 (0.21)
Apr 1,184,078 1,130,416 (4.53)
May 1,137,629 1,107,695 (2.63)
Jun 1,267,192 1,216,028 (4.04)
Jul 1,422,791
Aug 1,428,242
Sep 1,224,556
Oct 1,171,370
Nov 990,065
Dec 1,114,141
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
NoofPassengers
TIME (Month)
YVR International Airport
Forecast
Actual
R2
= 99.0 %
S.T.=4.52 (2010-2012)
2013(F)= 17,945,517Pax
Growth = 1.92
450,000
470,000
490,000
510,000
530,000
550,000
570,000
590,000
610,000
630,000
650,000
NoofPassengers
TIME (Month)
EIA International Airport
Forecast
Actual
R2
= 95.9 %
S.T.= 8.12 (2010-2012)
2013(F)= 6,881,180 Pax
Growth = 3.37
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1,500,000
NoofPassengers
TIME (Month)
MONTREAL International Airport
Forecast
Passengers Movements 2013
Actual
R2
= 97.0 %
S.T.= 7.18 (2010-2012)
2013(F) = 14,538,536 Pax
Growth = 5.53
Gander
St. John’s
Moncton
Charlottetown
Halifax
Saint John
Fredericton
Toronto
Ottawa
London
Montreal
Quebec
Thunder Bay
WinnipegRegina
Saskatoon
Calgary
Edmonton
Victoria
Vancouver
Prince George
CANADIAN AIRPORTS

Airports Forecasting28
Victoria International Airport
Jan 112,633 111,371 (1.12)
Feb 107,754 108,851 1.02
Mar 124,485 126,818 1.87
Apr 121,654 123,197 1.27
May 131,736 134,280 1.93
Jun 126,111 136,726 8.42
Jul 140,279 139,790 (0.35)
Aug 149,441 159,545 6.76
Sep 128,638
Oct 131,189
Nov 111,687
Dec 124,467
Ottawa Macdonald-Cartier International Airport
Jan 399,659 378,182 (5.37)
Feb 408,817 381,086 (6.78)
Mar 442,206 426,602 (3.53)
Apr 393,056 379,741 (3.39)
May 402,583 377,094 (6.33)
Jun 411,765 371,482 (9.78)
Jul 403,536 382,084 (5.32)
Aug 419,504
Sep 389,817
Oct 411,996
Nov 383,296
Dec 412,099
Winnipig International Airport
Jan 303,534 294,372 (3.02)
Feb 299,457 285,455 (4.68)
Mar 317,664 306,771 (3.43)
Apr 281,570 264,316 (6.13)
May 288,238 278,834 (3.26)
Jun 306,472 292,264 (4.64)
Jul 335,032
Aug 338,017
Sep 294,972
Oct 301,127
Nov 273,269
Dec 299,482
Kelowna International Airport
Jan 128,707 125,439 (2.54)
Feb 125,443 131,540 4.86
Mar 131,057 109,973 (16.09)
Apr 110,850 113,976 2.82
May 109,817 117,104 6.64
Jun 111,046 133,482 20.20
Jul 128,724 143,555 11.52
Aug 136,269
Sep 114,530
Oct 115,754
Nov 109,973
Dec 133,388
80,000
90,000
100,000
110,000
120,000
130,000
140,000
150,000
160,000
NoofPassengers
TIME (Month)
Victoria International Airport
Actual
Forecast
R2
= 96.7 %
S.T.= 3.87 (2010-2012)
2013(F)= 1,510,075 Pax
Growth = 0.21
300000
320000
340000
360000
380000
400000
420000
440000
460000
NoofPassengers
TIME (Month)
Ottawa Macdonald-Cartier International Airport
Forecast
Actual
R2 = 77.3 %
S.T.= 6.84 (2010-2012)
2013(F)= 4,878,335 Pax
Growth = 3.73
230,000
250,000
270,000
290,000
310,000
330,000
350,000
NoofPassengers
TIME (Month)
Winnipig International Airport
Actual
Forecast
R2
= 91.7 %
S.T.= 7.01 (2010-2012)
2013(F)= 3,638,834 Pax
Growth = 2.65
80,000
90,000
100,000
110,000
120,000
130,000
140,000
NoofPassengers
TIME (Month)
Kelowna International Airport
Forecast
Actual
R2
= 94.3 %
S.T.= 4.30 (2010-2012)
2013(F)= 1,455,559 Pax
Growth = 0.96

camamagazine.com
Calgary International Airport
Jan 1,072,551 1,092,390 1.85
Feb 1,047,803 1,052,912 0.49
Mar 1,164,374 1,187,811 2.01
Apr 1,128,212 1,144,194 1.42
May 1,137,530 1,151,024 1.19
Jun 1,176,611 1,160,841 (1.34)
Jul 1,350,627
Aug 1,358,582
Sep 1,170,418
Oct 1,149,343
Nov 1,063,522
Dec 1,144,130
Halifax International Airport
Jan 228,506 226,999 (0.66)
Feb 288,009 232,961 (19.11)
Mar 327,364 328,082 0.22
Apr 345,346 332,421 (3.74)
May 321,058
Jun 309,791
Jul 371,951
Aug 394,918
Sep 316,069
Oct 308,195
Nov 241,239
Dec 273,259
Deerlake Regional Airport
Jan 19,464
Feb 19,830
Mar 24,985
Apr 25,647
May 26,663
Jun 30,378
Jul 41,913
Aug 42,556
Sep 29,707
Oct 28,508
Nov 21,576
Dec 23,146
Total Forecast 334,371 Standard Error
Fort McMurray Airport
Jan 80,887 89,761 10.97
Feb 80,317 90,328 12.46
Mar 86,615 96,420 11.32
Apr 79,309 95,300 20.16
May 85,593 101,676 18.79
Jun 88,096 100,196 13.73
Jul 86,133 107,942 25.32
Aug 89,952
Sep 89,291
Oct 89,796
Nov 88,177
Dec 82,791
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
NoofPassengers
TIME (Month)
Calgary International Airport
Forecast
Actual
R2 = 97.8 %
S.T.= 7.65 (2010-2012)
2013(F)= 13,963,704 Pax
Growth = 2.80
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
NoofPassengers
TIME (Month)
Halifax International Airport
Forecast
Actual
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
NoofPassengers
TIME (Month)
Deerlake Regional Airport
Forecast
Actual
R2 = 98 %
S.T.= 5.24 (2010-2012)
2013(F)= 334,371 Pax
Growth = 9.27
40,000
50,000
60,000
70,000
80,000
90,000
100,000
NoofPassengers
TIME (Month)
Fort McMurray Airport
Forecast
Actual
R2
= 85.9 %
S.T.= 11.46 (2010-2012)
2013(F)= 1,026,957 Pax
Growth = 9.04
R
2
= 92.7 %
S.T.= 4.00 (2010 - 2012)
2013 (F) = 3,725,705 Pax
Growth = 2.92

HARD TARGET
Most of Airlines and Airports works on
achieving targets, and goals but at what
level they designs their targets, what are
their objectives, is it short term or long term
objectives, how to reflect the long term targets
with short term one, is it possible to build
seasonality model based on three years data
to match the trend forecasting results. How to
plan and develop a 3 in 1 strategy i.e mean
Trend target (10 years), Total Seasonality
Target (3 years) and Target that results from
International and Domestic (3 years)
3 in 1 Forecasting Strategy:
The idea of this strategy is how to achieve the
same target (figure) by different approaches,
in our case the trend target of 2013 for
traffic forecasting of all major US airports =
532,847,993 according to 2002-2012 annual
data base.
While for short range forecast of 2013 for Total
passengers based on 3 years that reflect 36
months (data set) is = 532,847,993 Further,
Total Passengers = International + Domestic
So the International traffic forecast of 2013 =
79,765,704 and
The Domestic traffic forecast of 2013 =
453,082,289 and by summation (Total) =
532,847,993
“There are two kinds of forecasters: those who
don’t know, and those who don’t know they
don’t know.”
John Kenneth Galbraith
Passenger Forecasting 2013
All Major US Airports (Seasonality Model)
30,000,000
35,000,000
40,000,000
45,000,000
50,000,000
55,000,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Developing 3 in 1 Forecasting Strategy –Airports Forecasting
34
R
2
= 98.5 %
S.T.= -33.31
2013 (F) = 532,847,993 Pax

2,700,000
2,900,000
3,100,000
3,300,000
3,500,000
3,700,000
3,900,000
4,100,000
4,300,000
4,500,000
4,700,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Atlanta, GA: Hartsﬁeld – Jackson Atlanta International Airport
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Miami, FL: Miami International Airports (Seasonality Model)
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
2,000,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Houston, TX: George Bush International/Houston Airport
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1,500,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Boston, MA: Logan International Airport
camamagazine.com
R
2
= 98 %
S.T.= 0.00
2013 (F) = 46,386,947 Pax
R
2
= 85.5 %
S.T.= 0.00
2013 (F) = 18,960,323 Pax
R
2
= 96.3 %
S.T.= 0.00
2013 (F) = 18,900,593 Pax
R
2
= 96.2 %
S.T.= 0.00
2013 (F) = 14,397,952 Pax

1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Charlotte, NC: Charlotte Douglas International Airport
1,200,000
1,700,000
2,200,000
2,700,000
3,200,000
3,700,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Chicago, IL: Chicago O’Hare International Airport
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
2,200,000
2,400,000
2,600,000
2,800,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Dallas/Fort Worth, TX: Dallas/Fort Worth International Airport
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
2,200,000
2,400,000
2,600,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Denver, CO: Denver International Airport
Airports Forecasting36
R
2
= 77.2 %
S.T.= 0.00
2013 (F) = 19,649,999 Pax
R
2
= 98.1 %
S.T.= 0.00
2013 (F) = 32,317,534 Pax
R
2
= 95.9 %
S.T.= 0.00
2013 (F) = 28,120,137 Pax
R
2
= 98.3 %
S.T.= 0.00
2013 (F) = 25,735,852 Pax

Detroit, MI: Detroit Metro Wayne Country Airport
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
-
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Minneapolis, MN: Minneapolis-St Paul International Airport
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
Las Vegas, NV: McCarran International Airport
Los Angeles, CA: Los Angeles International Airport
1,700,000
1,900,000
2,100,000
2,300,000
2,500,000
2,700,000
2,900,000
3,100,000
3,300,000
Jan-10
Apr-10
Jul-10
Oct-10
Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12
Oct-12
Jan-13
Apr-13
Jul-13
Oct-13
Jan-14
Apr-14
Jul-14
Oct-14
camamagazine.com
R
2
= 98.6 %
S.T.= 0.00
2013 (F) = 15,633,034 Pax
R
2
= 98.5 %
S.T.= 0.00
2013 (F) = 16,110,186 Pax
R
2
= 95.1 %
S.T.= 0.00
2013 (F) = 20,185,872 Pax
R
2
= 97.6 %
S.T.= 0.00
2013 (F) = 32,112,724 Pax

32
Research Scholar – Aviation ManagementForecasting by Objective
Case Study TALLINN Airport
To carry a traffic forecast for an airport is uneasy task, As
most of the statistician rely on coefficient of determination R2
to ensure the fairness of the analysis. In this article we will
try to create many scenarios that will reflects, what the top
management thinks, are they interesting to rely R2
(Classical
approach), are they trying to minimize the errors by setting
Signal Tracking to Zero, or trying to merge long range trend
forecast to be targeted (accumulated) for the seasonality
model, or to ask to follow the most update and recent
input data (recent years). Really all the four scenarios are
addressed, in case study of TALLINN Airport.
Case Study – TALLINN Airport:
Tallinn Airport (Estonian: Lennart Meri Tallinna lennujaam)
(IATA: TLL, ICAO: EETN) or Lennart Meri it formerly
Ülemiste Airport, is the largest airport in Estonia and home
base of the national airline Estonian Air. Tallinn Airport is
open to both domestic and international flights. It is located
approximately 4 km from the centre of Tallinn on the eastern
shore of Lake Ülemiste. As Tallinn is located nearest to Asia
Pacific of all EU capitals, this gives Tallinn Airport a major
geographical advantage for establishing long-haul flights
between these two regions.
Two set of data are examined to develop a Trend and
Seasonality Models.
A- Trend Model (15 years data set)
Based on these data the a trend model is developed and with
R2
= 86.1 and Signal Tracking = -1.84, the 2013 Forecasted
is = 2,495,900.
B- Seasonality Model (36 months data set)
Four Scenarios are developed as it is shown in the following
table.
1- Maximize R2
2- Setting Signal Tracking = Zero
3- Setting Trend Target to 2,495,900
4- Reflects the latest Input Data
Results:
All scenarios shows high values of R2
(all closes value) while
Signal Tracking shows a large divergence with respect to the
bond values and the best selection decision is scenario no. 3
(why) as it is almost cover three pre-constrained parameters
in spite of slight divergence of S. T. of the bond and also it
reflects the lowest one in the results.
Forecasted by Trend Target for 2013 = 2,495,900 Pax
R2
= 92.22%
Signal Tracking: 6.662
“The only true wisdom
is in knowing you know
nothing.”
Socrates
R
2
> 80% and -4 < T.S. < 4
-
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
y = 443370e0.108x
R2
= 0.861
2,495,900
TREND
ANALYSIS
No. Scenarios
Objective
?
Coefficient of
Determination
(R2
)
Signal
Tracking
(S. T.)
Forecasting
of
2013
Remarks
1 Maximize
R2
93.46% -33.31 2,907,888 -
2 Setting
S. T. = zero
92.67% 0.0000004 2,568,499 -
3 15 Years Tren
Target = 2,495,900
92,22% 6.662 2,495,900 Fair
4 Reflecting the
Latest Input Data
93.34% -26.26 2,794,463 -
TALLINN AIRPORT (Seasonlity Model)
Passengers Forecasting 2013
-
50,000
100,000
150,000
200,000
250,000
300,000
350,000
NoofPassengers
TIME (Month)
Forecast
Actual
Forecasting by Trend Target
R2 = 92.22 %
S.T.= 6.6620
Pax900,495,2(F) =2013
CAMA Magazine | issue 18 | March, 2013

33Airport forecasting
Washington Dulles International Airport
(IATA: IAD, ICAO: KIAD, FAA LID: IAD) is a public
airport in Dulles, Virginia, 26 miles (41.6 km) west of
downtown Washington, D.C. The airport serves the
Baltimore-Washington-Northern Virginia metropolitan
area centered on the District of Columbia. It is
named after John Foster Dulles, Secretary of State
under Dwight D. Eisenhower. The Dulles main
terminal is a well-known landmark designed by Eero
Saarinen. Operated by the Metropolitan Washington
Airports Authority, Dulles Airport occupies 11,830
acres (47.9 km2) straddling the border of Fairfax
County and Loudoun County, Virginia.
R
2
= 96.1
S.T.= 0.0
2013 (F) = 11,641,322 Pax
Detroit Metropolitan Wayne County Airport
(IATA: DTW, ICAO: KDTW), usually called Detroit
Metro Airport, Metro Airport locally, or simply
DTW, is a major international airport in the United
States covering 7,072-acre (11.050 sq mi; 2,862
ha) in Romulus, Michigan, a suburb of Detroit. It is
Michigan’s busiest airport and one of the world’s
largest air transportation hubs.
The airport serves as Delta’s second busiest hub.
Delta, along with SkyTeam partner Air France,
occupy the McNamara Terminal.
R
2
= 92.3
S.T.= -4
2013 (F) = 16,770,937 Pax
Forecasting of US Airports:
Airport forecasting is an important issue in
Aviation industry. It becomes an integral parts of
transportation planning. It sets targets and goals
for the airports, either for long term or medium term
planning. The primary statistical methods used in
airport aviation activity forecasting are market share
approach, econometric modeling, and time series
modeling.
While we will use R and Signal Tracking Approach.
Detroit Airport (Seasonlity Model)
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 92.3 %
S.T.= - 4
2013(F) = 16,770,937 Pax
Washington Dulles Airport (Seasonlity Model)
500,000
600,000
700,000
800,000
900,000
1,000,000
1,100,000
1,200,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 96.1%
S.T.= 0.0
2013(F) = 11,641,322 Pax

34
International Airport
(IATA: FLL, ICAO: KFLL, FAA LID: FLL) is
an international commercial airport located in
unincorporated Broward County, Florida, three miles
(5 km) southwest of the central business district of
Fort Lauderdale. It is also located near the city of
Hollywood and is 21 miles (33.7 km) north of Miami.
R
2
= 96.8
S.T.= 0.0
2013(F) = 12,080,874 Pax
Charlotte Douglas International Airport
(IATA: CLT, ICAO: KCLT, FAA LID: CLT) is a joint
civil-military public international airport located in
Charlotte, North Carolina. Established in 1935 as
Charlotte Municipal Airport, in 1954 the airport was
renamed Douglas Municipal Airport after former
Charlotte mayor Ben Elbert Douglas, Sr. The airport
gained its current name in 1982 and is currently US
Airways’ largest hub, with service to 175 domestic
and international destinations as of 2008. In 2009,
it was the 9th busiest airport in the United States
and in 2010, the 24th busiest airport in the world by
passenger traffic.
R
2
= 85.6
S.T.= 0
2013(F) = 21,135,269 Pax
Los Angeles International Airport
(IATA: LAX, ICAO: KLAX, FAA LID: LAX) is the
primary airport serving the Greater Los Angeles
Area, the second-most populated metropolitan area
in the United States. LAX is located in southwestern
Los Angeles along the Pacific coast in the
neighborhood of Westchester, 16 miles (26 km) from
the downtown core and is the primary airport of Los
Angeles World Airports (LAWA), an agency of the
Los Angeles city government formerly known as the
Department of Airports.
R
2
= 97.7
S.T.= 4
2013(F) = 32,269,576 Pax
Fort Lauderdale–Hollywood Airport (Seasonlity Model)
Charlotte Douglas Airport (Seasonlity Model)
Los Angeles Airport (Seasonlity Model)
600,000
700,000
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 96.8 %
S.T.= 0.00
2013(F) = 12,080,874 Pax
1,800,000
2,000,000
2,200,000
2,400,000
2,600,000
2,800,000
3,000,000
3,200,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 85.6 %
S.T.= 0.0
2013(F) = 21,135,269 Pax
1,800,000
2,000,000
2,200,000
2,400,000
2,600,000
2,800,000
3,000,000
3,200,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = ̂ 7.7 %
S.T.= 4
2013(F) = 32,269,576 Pax
Airport forecasting

Minneapolis–Saint Paul International Airport
(IATA: MSP, ICAO: KMSP, FAA LID: MSP) is a joint
civil-military public use airport. Located in a portion
of Hennepin County, Minnesota outside of any city
or school district, within ten miles (16 km) of both
downtown Minneapolis and downtown Saint Paul,
it is the largest and busiest airport in the five-state
upper Midwest region of Minnesota, Iowa, South
Dakota, North Dakota, and Wisconsin.
R
2
= 95.3%
S.T.= -3
2013(F) = 16,650,355 Pax
Chicago Midway International Airport
(IATA: MDW, ICAO: KMDW, FAA LID: MDW), is an
airport in Chicago, Illinois, United States, located on
the city’s southwest side, eight miles (13 km) from
Chicago’s Loop.
Dominated by low-cost carrier Southwest Airlines,
Midway is the Dallas-based carrier’s largest focus
city as of 2011. Both the Stevenson Expressway
and Chicago Transit Authority’s Orange Line provide
passengers access to downtown Chicago. Midway
Airport is the second largest passenger airport in the
Chicago metropolitan area, as well as the state of
Illinois, after Chicago O’Hare International Airport.
R
2
= 96%
S.T.= 4
2013(F) = 9,397,884 Pax
Dallas/Fort Worth International Airport
(IATA: DFW, ICAO: KDFW, FAA LID: DFW) is
located between the cities of Dallas and Fort Worth,
Texas, and is the busiest airport in the U.S. state
of Texas. It generally serves the Dallas–Fort Worth
metropolitan area.
DFW is the fourth busiest airport in the world in
terms of aircraft movements. In terms of passenger
traffic, it is the eighth busiest airport in the world. It
is the largest hub for American Airlines. DFW Airport
is considered to be an Airport City.
R2
= 97.3%
S.T.= 0.76
2013 (F) = 28,183,463 Pax
35
Dallas Airport (Seasonlity Model)
Minneapolis–Saint Paul Airport (Seasonlity Model)
Chicago Midway Airport (Seasonlity Model)
1,600,000
1,800,000
2,000,000
2,200,000
2,400,000
2,600,000
2,800,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = ̂ 7.3 %
S.T.= 0.75
2013(F) = 28,183,463 Pax
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = ̂ 5.˼ %
S.T.= - 3
2013(F) = 16,650,355 Pax
400,000
500,000
600,000
700,000
800,000
900,000
1,000,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 96.1%
S.T.= 0.0
2013(F) = 9,397,884 Pax
Airport forecasting

30
Getting The Right Picture
Head to Head analysis
Seasonally Adjusted Vs Seasonally Fitted
Furthers to my previous articles, this
article will address the difference and
compare the Seasonally Adjusted
technique Vs Seasonally Fitted. Basically
Forecasting model can be defined by four
components i.e Trend, Cyclical, Seasonal,
and Irregular.
A model that treats the time series
values as a sum of the components is
called an additive component model
(Yt=Tt+Ct+St+It) , While a model that treats
the time series values as a product of
the components is called a multiplicative
component model (Yt=Tt×Ct×St×It)
Seasonally Adjusted:
Most economic series published by
international Organizations ( IATA, ICAO)
are seasonally adjusted because seasonal
variation is not of primary interest.
Rather, it is the general patterned of
economic activity, independent of normal
seasonal fluctuation that is of interest. So
seasonally adjusted is done to simplify
data so that they may be more easily
interpreted by statistically unsophisticated
users without a significant loss of
information. e.g – IATA Forecasting.
Seasonally Fitted:
General guidance, we set a constrains to
measure the Goodness of Fit, this time
we use R and Signal Tracking ( R ≥ 80
and 4 ≥ S.T.≥ -4 ). The seasonal model
fairly fitted by defining and controlling two
main factors for mapping the figure, first is
Displacement Factor which can be defined
by the value of signal tracking, it is either
upper or lower of the base forecasting
line. Where the second factor is the
rotating angle and that can be monitor by
the value of R i.e why both R and signal
tracking are displayed in the graph.
Summary:
Both methods are fair, so to get the
general trend, we use seasonally adjusted
but to ensure to get the right picture we
have to define the seasonality patterned
and define their accuracy measuring
factors in terms of R and Signal
Tracking, the issue of this method only
its applicability for short range period 1-3
years if we exceed the time/period the
program should modified and set a new
one.
CAMA Magazine | issue 17 | December, 2012
billion’s monthly f/cast
Actual Seasonally Adjusted Forcast
R
2
= 90%
Tracking Signal = -0.0000028
Time
billion’smonthly
International scheduled passenger traffic (RPKs) Industry total
Latest data April 2011
Time
Oumra
Session
Hajj
Session
Summer
Session
Winter
Session
Actual Year
Cycle
Forecasted Year
Cycle
Sales/Passengers
Back to school
Session
“Facts are Many
but the Truth is
One.”
Rabindranath Tagore
IATA
IATA

31
Airports Forecasting:
modeling.
Model Used:
Based on a historical data of the airports, (3 years
on monthly bases) the mathematical model is
developed where its fairness and goodness of fit can
be defined by two important factors:
R
2
(Coeff. Of Determination) > 80%
S. T (Signal Tracking) ..(- 4 ≥ S.T. ≤ 4)
This time we try to set (S.T.) to Zero
Oslo Airport, Gardermoen
(Norwegian: Oslo lufthavn, Gardermoen; IATA:
OSL, ICAO: ENGM), also known as Gardermoen
Airport, is the principal airport serving Oslo, the
capital of and most populous city in Norway. Oslo is
also served by the low-cost Torp Airport and Rygge
Airport. Gardermoen acts as the main domestic
hub and international airport for Norway, and is the
second-busiest airport in the Nordic countries.
R2
= 93%, S.T.= 0
2013 (F) = 23,717,975 Pax
Munich Airport
(IATA: MUC, ICAO: EDDM) (German: Flughafen
München), is an international airport located 28.5
km (17.7 mi) northeast of Munich, Germany, and
is a hub for Lufthansa and Star Alliance partner
airlines. It is located near the old city of Freising and
is named in memory of the former Bavarian Prime
minister Franz Josef Strauss. The airport is located
on the territory of four different municipalities:
Oberding (location of the terminals; district of
Erding), Hallbergmoos, Freising and Marzling
(district of Freising).
R
2
= 94%, S.T.= 0
2013 (F) = 42,565,394 Pax
Paris Orly Airport
(French: Aéroport de Paris-Orly) (IATA: ORY, ICAO:
LFPO) is an international airport located partially in
Orly and partially in Villeneuve-le-Roi, 7 NM (13 km;
8.1 mi) south of Paris, France. It has flights to cities
in Europe, the Middle East, Africa, the Caribbean,
North America and Southeast Asia. Prior to the
construction of Charles de Gaulle Airport, Orly was
the main airport of Paris.
R
2
= 91%, S.T.= 0
2013 (F) = 29,120,442 Pax
Oslo Airport
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
2,200,000
2,400,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 93 %
S.T.= 0
2013(F) = 23,717,975 Pax
Munich Airport
1,200,000
1,700,000
2,200,000
2,700,000
3,200,000
3,700,000
4,200,000
4,700,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 94 %
S.T.= 0
2013(F) = 42,565,394 Pax
Orly Airport
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
2,200,000
2,400,000
2,600,000
2,800,000
3,000,000
3,200,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 91 %
S.T.= 0
2013(F) = 29,120,442 Pax
Airport forecasting

32
Edinburgh Airport
(Scottish Gaelic: Port-adhair Dhùn Èideann) (IATA:
EDI, ICAO: EGPH) is located at Turnhouse in the
City of Edinburgh, Scotland, and was the busiest
airport in Scotland in 2011, handling just under 9.4
million passengers in that year. It was also the sixth
busiest airport in the UK by passengers and the
fifth busiest by aircraft movements. It is located 5
nautical miles (9.3 km; 5.8 mi) west of the city centre
and is situated just off the M8 motorway.
R
2
= 93%
S.T.= 0
2013(F) = 9,688,572 Pax
Avinor – (airports traffic)
AS is a state-owned limited company that operates
most of the civil airports in Norway. The Norwegian
state, via the Norwegian Ministry of Transport and
Communications, controls 100 percent of the share
capital. Avinor was created on 1 January 2003, by
the privatization of the Norwegian Civil Aviation
Administration known as Luftfartsverket. Its head
office is in Bjørvika, Oslo, located on the seaside of
Oslo Central Station.
R
2
= 92%
S.T.= 0
2013(F) = 49,847,034 Pax
Gold Coast Airport, or Coolangatta Airport
(IATA: OOL, ICAO: YBCG) is an Australian domestic
and international airport at the southern end of the
Gold Coast, some 100 km (62 mi) south of Brisbane
and 25 km (16 mi) south of Surfers Paradise. The
entrance to the airport is situated in the suburb
of Bilinga on the Gold Coast. The runway itself
straddles five suburbs of twin cities across the state
border of Queensland and New South Wales. During
summer these states are in two different time zones.
R
2
= 0.64%
S.T.= 0
2013(F) = 5,551,812 Pax
Edinburgh Airport
Avinor Airport
Gold Coast Airport
400,000
500,000
600,000
700,000
800,000
900,000
1,000,000
1,100,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 93 %
S.T.= 0
2013(F) = 9,688,572 Pax
2,200,000
2,700,000
3,200,000
3,700,000
4,200,000
4,700,000
5,200,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 92 %
S.T.= 0
2013(F) = 49,847,034 Pax
300,000
350,000
400,000
450,000
500,000
550,000
600,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 0.64 %
S.T.= 0
2013(F) = 5,551,812 Pax
Airport forecasting

Cairns Airport
(IATA: CNS, ICAO: YBCS) is an international airport
in Cairns, Queensland, Australia. Formerly operated
by the Cairns Port Authority, the airport was sold
by the Queensland Government in December 2008
to a private consortium. It is the seventh busiest
airport in Australia. The airport is located 2.3 nautical
miles (4.3 km; 2.6 mi) north northwest [1] of Cairns
or 7 kilometres (4.3 mi) north of the Cairns central
business district, in the suburb of Aeroglen. The
airport lies between Mount Whitfield to the west and
Trinity Bay to the east.
R
2
= 92%
S.T.= 0
2013(F) = 4,297,288 Pax
[1] http://en.wikipedia.org/wiki/Main_Page
Melbourne Airport
(IATA: MEL, ICAO: YMML), also known as
Tullamarine Airport, is the primary airport serving
the city of Melbourne, and the second busiest airport
in Australia. It was opened in 1970 to replace the
nearby Essendon Airport. Melbourne Airport is the
sole international airport of the four airports serving
the Melbourne metropolitan area.
The airport is 23 km (14 mi) from the city centre. The
airport has its own postcode—Melbourne Airport,
Victoria (postcode 3045). This is adjacent to the
suburb of Tullamarine.
R
2
= 83%
S.T.= 0
2013(F) = 29,942,351 Pax
Brisbane Airport
(IATA: BNE, ICAO: YBBN) is the sole passenger
airport serving Brisbane and is the third busiest
airport in Australia after Sydney Airport and
Melbourne Airport. Brisbane Airport has won
many awards. Brisbane is currently served with 46
domestic destinations in all States and Territories
and 32 international destinations. For the 12 months
ending May 2011 total passengers were 20,056,416.
R2
= 93%
S.T.= 0
2013(F) = 21,932,169 Pax
33
Brisbane Airport
Cairns Airport
Melbourne Airport
1,200,000
1,300,000
1,400,000
1,500,000
1,600,000
1,700,000
1,800,000
1,900,000
2,000,000
2,100,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 93 %
S.T.= 0
2013(F) = 21,932,169 Pax
200,000
250,000
300,000
350,000
400,000
450,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 92 %
S.T.= 0
2013(F) = 4,297,288 Pax
1,800,000
1,900,000
2,000,000
2,100,000
2,200,000
2,300,000
2,400,000
2,500,000
2,600,000
2,700,000
2,800,000
NoofPassengers
TIME (Month)
Forecast
Actual
R2 = 83 %
S.T.= 0
2013(F) = 29,942,351 Pax
Airport forecasting

28
Matching Long Range Data Targets
By Short Range Data Targets
“Plans are
nothing;
planning is
everything.”
Dwight D. Eisenhower
Forecasting is the right tool for a fair decision making, we use it to create a proper plans
,activities and setting up budgets. But what is the right effective model, what are the
right parameters to measure the goodness of fits, and how to plan to match the long
range targets by a short range targets, can we get same answer from different models.
This is what we will address it in….
Nice Airport Case Study:
1- Developing Long Range Targets:
Trend Model:
Based on annual historical data period (1950-2011)
Input Data: 51 sets (Annually)
Coefficient of Determination: 99.6%
Signal Tracking: 0.0000011
Results:
Passengers Forecast 2012= 10,467,360
2- Developing Short Range Targets:
Seasonality Model:
Based on monthly 3 years data period (2009-2011)
Input Data: 36 sets (Monthly)
Coefficient of Determination: 96.7%
Signal Tracking: -30.14
Results:
Summary:
The results are fairly matched, so it possible to plan in such a way that, we utilize the
annual trends to meet the annual cumulative forecast of the seasonality model for two
forecasted years, keeping in mind the pre-request constrains for both models.
400000
500000
600000
700000
800000
900000
1000000
1100000
1200000
1300000
NoofPassengers
TIME (Month)
Forecast
Actual
0
2000000
4000000
6000000
8000000
10000000
12000000
Passengers
Years
Forecast
Passengers
Forecasting 2012, 2013
Seasonlity Model
1950 - 2011 Passengers
Coefficient of
Determination = 0.996
Signal Tracking = 0.0000011
R
2
= 96.7%
S.T.= -30.17
2012 (F)= 10,467,360 Pax
2013 (F)= 10,493,391 Pax
2012(F)= 10,467,360 Pax
2013(F)= 10,493,391 Pax
CAMA Magazine | issue 16 | September, 2012

29AIRPORTS Forecasting
modeling.
Model Used:
BaBased on a historical data of the airports, (3
years on monthly bases) the mathematical model is
R
2
S. T (Signal Tracking) ..(-4 < S.T. < 4)
This time we try to set (S.T.) to Zero
Airport Performances:
There are many factors that may measure the airport
performance, mainly:
1) Number of Passengers
2) Aircraft Movement and;
3) Freight
SANA’A Airport
Sana’a International Airport or El Rahaba Airport
(Sana’a International) (IATA: SAH, ICAO: OYSN) is
an international airport located in Sana’a, the capital
of Yemen. Recently Yemen passes in a transition
phase, as results a democracy. This situation effects
on 2011 data base.
So the basic analysis addressing 2008, 2009, and
2010. And the forecasted period are 2011 and 2012.
But in this issue we are addressed the Yemenia and
Other Operators
Yemenia:
Passenger Forecasting 2012 = 764,398 Pax
Peak Periods: July-August
Annual Growth : (0.02) %
The Model is not fair as R = 44%
Other Operators:
Passenger Forecasting 2012 = 600513Pax
Peak Periods: July
Annual Growth : 0.08 %
Total –
Yemenia and Other Operators
Passenger Forecasting 2012 = 1,340,118Pax
Peak Periods: July - August
yemen Airports
Sanaa Airport, Forecasting 2011, 2012
Seasonlity Model (Other Carriers)
Seasonlity Model (Yemenia)
Seasonlity Model (IY + Other Carriers)
20000
25000
30000
35000
40000
45000
50000
55000
60000
65000
70000
NoofPassengers
TIME (Month)
Forecast
Actual
80000
90000
100000
110000
120000
130000
140000
150000
160000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 77%
S.T.= 00
2012(F) = 600,513 Pax
Annual Growth : 0.08
R
2
= 66%
S.T.= -0.00
2012(F)= 1,340,118 Pax
Annual Growth : 0.01
40000
50000
60000
70000
80000
90000
100000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 44%
S.T.= 00
2012(F)= 764,398 Pax
Annual Growth: (0.02)

30 AIRPORTS Forecasting
international Airports
Paris-Charles de Gaulle Airport
(IATA: CDG, ICAO: LFPG) (French: Aéroport Paris-
Charles de Gaulle), is one of the world’s principal
aviation centers, as well as France’s largest airport.
It is named after Charles de Gaulle (1890–1970),
leader of the Free French Forces and founder of the
French Fifth Republic. It is located within portions of
several communes, 25 km (16 mi) to the northeast
of Paris. The airport serves as the principal hub for
Air France. In 2011, the airport handled 60,970,551
passengers and 514,059 aircraft movements,
making it the world’s sixth busiest airport and
Europe’s second busiest airport (after London
Heathrow) in passengers served.
Passenger Forecasting 2012= 62,166,461 Pax
Annual Growth: 2.6%
The Model is fair fitted as R
2
= 93%
Denver International Airport
(IATA: DEN, ICAO: KDEN, FAA LID: DEN), often
referred to as DIA, is an airport in Denver, Colorado.
In 2011 Denver International Airport was the 11th-
busiest airport in the world by passenger traffic with
52,699,298 passengers. It was the fifth-busiest
airport in the world by aircraft movements with over
635,000 movements in 2010.. Denver International
Airport is the main hub for low-cost carrier Frontier
Airlines and commuter carrier Great Lakes Airlines. It
is also the fourth-largest hub for United Airlines.
Passenger Forecasting 2012 = 53,986,884 Pax
Annual Growth: 2.21%
2
= 97.7%
Chicago O’Hare International Airport
(IATA: ORD, ICAO: KORD, FAA LID: ORD), also
known as O’Hare Airport, O’Hare Field, Chicago
Airport, Chicago International Airport, or
simply O’Hare, is a major airport located in the
northwestern-most corner of Chicago, Illinois, United
States. prior to 1998, O’Hare was the busiest airport
in the world in terms of the number of passengers.
O’Hare has a strong international presence, with
flights to more than 60 foreign destinations: it is the
fourth busiest international gateway in the United
States behind John F. Kennedy International Airport
in New York City, Los Angeles International Airport
and Miami International Airport.
Annual Growth: 1.34 %
2
= 97.3%
Seasonlity Model
Seasonlity Model
Seasonlity Model
3000000
3500000
4000000
4500000
5000000
5500000
6000000
6500000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 93 %
S.T.= 0
2012(F)= 62,166,461 Pax
2013 (F)= 63,812,317 Pax
Annual Growth= 2.6%
3000000
3500000
4000000
4500000
5000000
5500000
6000000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 97.7 %
S.T.= 0
2012 (F)= 53,986,884 Pax
2013 (F)= 55,184,393 Pax
3000000
3500000
4000000
4500000
5000000
5500000
6000000
6500000
7000000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 97.3%
S.T.= 0.00
2012 (F)= 67,859,340 Pax
2013 (F)= 68,773,005 Pax

Edmonton International Airport
(IATA: YEG, ICAO: CYEG) is the primary air
passenger and air cargo facility in the Edmonton
region of the Canadian province of Alberta. It is
a hub facility for Northern Alberta and Northern
Canada, providing regularly scheduled nonstop
flights to over fifty communities in Canada, the
United States, Latin America and Europe. It is one
of Canada’s largest airports by total land area, the
5th busiest airport by passenger traffic, and the
10th busiest by aircraft movements. Operated by
Edmonton Airports and located 14 NM (26 km; 16
mi) south southwest of downtown Edmonton, in
Leduc County, and adjacent to the City of Leduc, it
served over 6.2 million passengers in 2011.
The Model is fair fitted as R2 = 91.9 %
London Heathrow Airport or Heathrow
(IATA: LHR, ICAO: EGLL) is a major international
airport serving London, England, United Kingdom.
Located in the London Borough of Hillingdon, in
West London, Heathrow is the busiest airport in
the United Kingdom and the third busiest airport in
the world (as of 2012) in terms of total passenger
traffic, handling more international passengers than
any other airport around the globe. It is also the
busiest airport in the EU by passenger traffic and the
third busiest in Europe given the number of traffic
movements, with a figure surpassed only by Paris-
Charles de Gaulle Airport and Frankfurt Airport.
The Model is fair fitted as R2 = 89 %
Nice Côte d’Azur Airport
(IATA: NCE, ICAO: LFMN) is an airport located
3.2 NM (5.9 km; 3.7 mi) southwest of Nice, in the
Alpes-Maritimes department of France. The airport
is positioned 7 km (4 mi) west of the city centre,
and is the principal port of arrival for passengers
to the Côte d’Azur. It is the third busiest airport in
France after Charles de Gaulle International Airport
and Orly Airport, both in Paris. Due to its proximity
to the Principality of Monaco, it also serves as the
city-state’s airport, Some airlines marketed Monaco
as a destination via Nice Airport. it is also serves as
a hub for Air France.
The Model is fair fitted as R2 = 98.3 %
Seasonlity Model
Seasonlity Model
Seasonlity Model
400000
500000
600000
700000
800000
900000
1000000
1100000
1200000
1300000
NoofPassengers
TIME (Month)
Forecast
Actual
Optimum Solution
R
2
= 98.3 %
S.T.= 0
2012 (F)= 10,496,380 Pax
2013 (F)= 10,772,005 Pax
450000
470000
490000
510000
530000
550000
570000
590000
610000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 91.9%
S.T.= 0
2012(F)= 6,329,057 Pax
2013 (F)= 6,419,625 Pax
Annual Growth= 1.4%
4000000
4500000
5000000
5500000
6000000
6500000
7000000
7500000
NoofPassengers
TIME (Month)
Forecast
Actual
R
2
= 89%
S.T.= 0
2012(F)= 70,557,827 Pax
2013(F)= 72,406,685 Pax
Annual Growth: 2.6%

30
Researcher in Aviation science
“The golden rule is that
there are no golden
rules”
George Bernard Shaw
Figure (1). Recommended Forecasting Methods
Measuring Forecast Accuracy
Coefficient of Determination (R2 ) Vs Signal Tracking ( S. T.)
Usually in practicing forecast, the golden rule for fitting data is to define R2 as the best
indicator, this statement is not perfectly right ... why !!!!! It may indicate that, there is
relation between two sets of data, but not with minimizing errors, this can be explained
clearly by Turkish Airline data as shown in the figure (1),
The process started by a normal forecasting procedure and by test the Goodness of Fit
and calculating R2, then reduce the forecasting results by 500 and test the Goodness
of Fit by calculating R2, again reduce the forecasting results now by 1000 and test the
Goodness of Fit by calculating R2 . You will find that R2 is same for the three trails
which is (97%) this prove that R2 just indicate a relation between two set of data.
While there is another factor that refine the final results this factor is S. T. (Signal
Tracking). Which control and set to the acceptable level (Zero).
so Error = Actual Passengers – Forecast
Or et = At – Ft
while there are many other factors as:
Mean Forecast Error (MFE)
For n time periods where we have actual demand and forecast values:
Ideal value = 0;
MFE > 0, model tends to under-forecast
MFE < 0, model tends to over-forecast
Mean Absolute Deviation (MAD)
For n time periods where we have actual demand and forecast values:
While MFE is a measure of forecast model bias, MAD indicates the absolute size of the
errors
Tracking Signal
Used to pinpoint forecasting models that need adjustment
As long as the tracking signal is between –4 and 4, assume the model is working
correctly.
In this analysis, we control the value of Tracking Signal to be Zero while R is evaluated
normally provided that it should be greater than 80%
-
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
01-Jan-09
01-Mar-09
01-May-09
01-Jul-09
01-Sep-09
01-Nov-09
01-Jan-10
01-Mar-10
01-May-10
01-Jul-10
01-Sep-10
01-Nov-10
01-Jan-11
01-Mar-11
01-May-11
01-Jul-11
01-Sep-11
01-Nov-11
01-Jan-12
01-Mar-12
01-May-12
01-Jul-12
01-Sep-12
01-Nov-12
01-Jan-13
01-Mar-13
01-May-13
01-Jul-13
01-Sep-13
01-Nov-13
No.ofPassengersx1000
TIME
Turkish Airline - Trafﬁc Forecasting 2012
Forecast -500
Forecast-1000
Actual
Forecast
All are same ( R2 ) = 97 %
S.T.= are different
2012(F) = …………… PAX

modeling.
Model Used:
Based on a historical data of the airports, (3 years
on monthly bases) the mathematical model is
R
2
S. T (Signal Tracking) ..(-4 < S.T. < 4)
This time we set (S.T.) to Zero
There are many factors that may measure the airport
performance, mainly:
2) Aircraft Movement and;
3) Freight
SANA’A Airport
Sana’a International Airport or El Rahaba Airport
(Sana’a International) (IATA: SAH, ICAO: OYSN) is
an international airport located in Sana’a, the capital
of Yemen. Recently Yemen passes in a transition
phase, as results a democracy. This situation effects
on 2011 data base.
So the basic analysis addressing 2008, 2009, and
2010. And the forecasted period are 2011 and 2012.
But in this issue we are addressed the Domestic
segment.
Passenger Forecasting 2012 = 688,596 Pax
Peak Periods: not properly defined
Annual Growth : 19 %
The Model is good as R = 77%
Aircraft Movement Forecasting 2012 = 19,983
Peak Periods: not properly defined
Annual Growth: 29%.
The Model is hardly fitted as R = 73%
Freights &Mails Forecasting 2012 = 689 Tone. Peak
Periods: not properly defined
Annual Growth: - 5 %.
The Model reflects a lot of discrepancies as R = 45%
with a negative trends and growth, so results should
be take in caution.
yemen Airports
-
10,000
20,000
30,000
40,000
50,000
60,000
70,000
NoofPassengers
TIME (Month)
SANA'A Airport (Seasonlity Model)
Domestic Passengers Forecasting 2012
Forecast
Actual
-
20
40
60
80
100
120
140
160
01-Jan-08
01-Mar-08
01-May-08
01-Jul-08
01-Sep-08
01-Nov-08
01-Jan-09
01-Mar-09
01-May-09
01-Jul-09
01-Sep-09
01-Nov-09
01-Jan-10
01-Mar-10
01-May-10
01-Jul-10
01-Sep-10
01-Nov-10
01-Jan-11
01-Mar-11
01-May-11
01-Jul-11
01-Sep-11
01-Nov-11
01-Jan-12
01-Mar-12
01-May-12
01-Jul-12
01-Sep-12
01-Nov-12
Freight+Mails
TIME (Month)
Freight & Mails inTonne Forecasting 2012
Forecast
Actual
-
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
01-Jan-08
01-Mar-08
01-May-08
01-Jul-08
01-Sep-08
01-Nov-08
01-Jan-09
01-Mar-09
01-May-09
01-Jul-09
01-Sep-09
01-Nov-09
01-Jan-10
01-Mar-10
01-May-10
01-Jul-10
01-Sep-10
01-Nov-10
01-Jan-11
01-Mar-11
01-May-11
01-Jul-11
01-Sep-11
01-Nov-11
01-Jan-12
01-Mar-12
01-May-12
01-Jul-12
01-Sep-12
01-Nov-12
NoofLanding
TIME (Month)
Aircraft Movement Forecasting 2011-2012
Forecast
Actual
R
2
= 45%
S.T.= -0.00
2012(F)= 689
Annual Growth: - 0.05
R
2
= 73%
S.T.= -0.00
2012(F)= 19,983
Annual Growth= 0.29
R
2
= 77%
S.T.= -0.00
2012(F)= 688,596
Annual Growth: 0.19

ARABIC Airports
Doha International Airport
(IATA: DOH, ICAO: OTBD) is the only commercial
airport in Qatar.. There are 60 check-in gates, 8
baggage claim belts and over 1,000 car parking
spaces.. As of 2010, it was the world’s 27th busiest
airport by cargo traffic. The existing airport will be
replaced in early 2013 when the first phase of New
Doha International Airport is expected to open. The
new airport is located 4 km from the current facility.
It covers 5400 acres (approx. 2200 hectares) of land
and will be able to handle 12.5 million passengers
per year after the first phase of construction is
completed. The airport is currently ranked as a
3-star by Skytrax.
Annual Growth: 13%
The Model is fairly fitted as R
2
= 96%.
Queen Alia International Airport
(IATA: AMM, ICAO: OJAI) is Jordan’s largest
airport that is situated in Zizya (‫)زيزياء‬ area, 20 miles
(32 km) south of Amman. The airport has three
terminals: two passenger terminals and one cargo
terminal. It is the main hub of Royal Jordanian
Airlines, the national flag carrier, as well as being a
major hub for Jordan Aviation. It was built in 1983
and is named after Queen Alia, the third wife of the
late King Hussein of Jordan.
Annual Growth: 4%
2
= 88%.
Beirut Rafic Hariri International Airport
(formerly Beirut International Airport; IATA:
BEY, ICAO: OLBA; is located 9 kilometres (5.6
mi) from the city centre in the southern suburbs
of Beirut, Lebanon and is the only operational
commercial airport in the country. It is the hub for
Lebanon’s national carrier, Middle East Airlines.
It is also the hub for the Lebanese cargo carrier
Trans Mediterranean Airways, as well as the charter
carriers Med Airways and Wings of Lebanon. The
airport was selected by “Skytrax Magazine” as the
second best airport and aviation hub in the Middle
East; it came behind Dubai International Airport.
Annual Growth: 3%
2
= 94%.
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
NoofPassengers
TIME (Month)
QAIA Airport (Seasonlity Model)
Forecast
Actual
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
NoofPassengers
TIME (Month)
Beirut Airport (Seasonlity Model)
Forecast
Actual
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
NoofPassengers
TIME (Month)
Beirut Airport (Seasonlity Model)
Forecast
Actual
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
2,200,000
NoofPassengers
TIME (Month)
Doha Airport (Seasonlity Model)
Forecast
Actual
R
2
= 94%
S.T.= 0.00
2012(F)= 5,669,461
Annual Growth= 0.03
R
2
= 88%
S.T.= 0.00
2012(F)= 5,623,315
Annual Growth= 0.04
R
2
= 96%
S.T.= 0.00
2012(F)= 19,841,946
Annual Growth= 0.13

Geneva International Airport
(IATA: GVA, ICAO: LSGG), formerly known as
Cointrin Airport and officially as Genève Aéroport,
is an airport serving Geneva, Switzerland. It is
located 4 km (2.5 mi) northwest of the city centre. It
is a major hub for EasyJet Switzerland and Darwin
Airline, a lesser hub for Swiss International Air Lines
and the former hub of Swiss World Airways, which
ceased operations in 1998. Geneva International
Airport has extensive convention facilities and
hosts an office of the International Air Transport
Association (IATA) and the world headquarters of
Airports Council International (ACI).
Annual Growth: 6%
2
= 91%
Sydney (Kingsford Smith) Airport (also known as
Kingsford-Smith Airport and Sydney Airport)
(IATA: SYD, ICAO: YSSY) (ASX: SYD) is located in
the suburb of Mascot in Sydney, Australia. It is the
only major airport serving Sydney, and is a primary
hub for Qantas, as well as a secondary hub for
Virgin Australia and Jetstar Airways. Sydney Airport
is one of the oldest continually operated airports
in the world, and the busiest airport in Australia,
handling 36 million passengers in 2010 and 289,741
aircraft movements in 2009. It was the 28th busiest
airport in the world in 2009. Currently 47 domestic
destinations are served to Sydney direct.
Annual Growth: 2%
2
= 84%
Annual Growth: 6.1%
2
= 96%
Montréal-Pierre Elliott Trudeau International
Airport
(IATA: YUL, ICAO: CYUL), formerly known as
Montréal-Dorval International Airport, is located on
the Island of Montreal. It is the busiest airport in
the province of Quebec, the third busiest airport in
Canada by passenger traffic and fourth busiest by
aircraft movements, with 13,660,862 passengers in
2011 and 217,545 movements in 2010. and it is one
of the main gateways into Canada with 8,436,165
or 61.7% of its passengers being on non-domestic
flights.
Annual Growth: 5%
The Model is fair fitted as R2
= 97%
2,400,000
2,600,000
2,800,000
3,000,000
3,200,000
3,400,000
NoofPassengers
TIME (Month)
Sydney Airport (Seasonlity Model)
Forecast
Actual
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
NoofPassengers
TIME (Month)
Montréal Airport (Seasonlity Model)
Forecast
Actual
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
NoofPassengers
TIME (Month)
Genève Airport (Seasonlity Model)
Forecast
Actual
R
2
= 84%
S.T.= 0.00
2012(F)= 36,346,492
Annual Growth= 0.02
R
2
= 91%
S.T.= 0.00
2012(F)= 13,622,031
Annual Growrh = 0.06
R
2
= 97%
S.T.= 0.00
2012(F)= 14,251,824
Annual Growth= 0.05

30
Airport Forecasting
Forecasts of airport aviation activity have become an integral
part of transportation planning. Most airport-specific forecasts
are prepared on behalf of airport sponsors and state or regional
agencies. The type and method of forecasting can depend
importantly on the purpose for which the forecast is being made.
The primary statistical methods used in airport aviation
activity forecasting include market share analysis, econometric
modeling, and time series modeling. These methods can be
used to create forecasts of future airport activity over time.
Simulation models are a separate method of analysis used to
provide snapshot estimates of traffic flows across a network or
through an airport.
The main measuring performance factors for airports
are traffic passengers, aircraft movements and freight. And
consequently these factors are breakdown to sublevels in term
of departures, arrivals and transit activities.
Forecasting Methods
The majority of airport and regional and state aviation activity
studies use fairly simple methods to produce forecasts, and
address forecast uncertainty only in informal and nonsystematic
ways. Figure (1). Summary of Recommended Forecasting
Methods.
Researcher in Aviation science
Purpose of Activity Forecast
Historical Data Availability
Increasing Data Requirements
Stable Trend
Stable Relationship with:
External Forecasts Causal Variables
Short-Term Operational Planning:
Annual Budgeting
Time series trend extrapolation, or
smoothing/Box-Jenkins if complex
time dependencies
Market Share Forecasting Econometric Modeling
Identify Long-Term Capacity Needs:
Financial Planning to Support Facility
Expansion
Market share forecasting or
econometric modeling
Market Share Forecasting Econometric Modeling
Examine Alternative Environment:
Compare Alternative Policies
Econometric Modeling
Obtain High-Fidelity Estimates of
Travel Time and Delays (Aircraft or
Passengers)
Simulation Modeling
“The easiest way to
predict the future is to
invent it.”
Immanuel Kant - German Philosopher
Reference: Aviation Forecasting - FAA
AIRPORTS
Forecasting
Figure (1). Recommended Forecasting Methods
AIRPORTS Forecasting

Passengers Forecasting 2011-2012
100,000
120,000
140,000
160,000
180,000
200,000
220,000
NoofTotalPassangers
TIME (Month)
Forecast
Actual
R2 = 78 %
S.T.= -2.02
2012(F) = 2,048,088 Pax
01/01/2008
01/04/2008
01/07/2008
01/10/2008
01/01/2009
01/04/2009
01/10/2009
01/10/2009
01/01/2010
01/04/2010
01/07/2010
01/10/2010
01/01/2011
01/04/2011
01/07/2011
01/10/2011
01/01/2012
01/04/2012
01/07/2012
01/10/2012
Aircraft Movement Forecasting 2011-2012
1,400
1,800
2,200
2,600
3,000
3,400
3,800
Noof(Landing+Takeoff)
Forecast
Actual
R2 = 94 %
S.T.= -12.65
2012(F) = 39,606
TIME (Month)
01/01/2008
01/03/2008
01/05/2008
01/07/2008
01/09/2008
01/11/2008
01/01/2009
01/03/2009
01/05/2009
01/07/2009
01/09/2009
01/11/2009
01/01/2010
01/03/2010
01/05/2010
01/07/2010
01/09/2010
01/11/2010
01/01/2011
01/03/2011
01/05/2011
01/07/2011
01/09/2011
01/11/2011
01/01/2012
01/03/2012
01/05/2012
01/07/2012
01/09/2012
01/11/2012
Freights & Mails Forecasting 2011-2012
1,000
1,200
1,400
1,600
1,800
2,000
2,200
2,400
Freight+Mail(Tonne)
Forecast
Actual
R2 = 38 %
S.T.= -3.02
2012(F) = 23493 Tonne
TIME (Month)
01/01/2008
01/03/2008
01/05/2008
01/07/2008
01/09/2008
01/11/2008
01/01/2009
01/03/2009
01/05/2009
01/07/2009
01/09/2009
01/11/2009
01/01/2010
01/03/2010
01/05/2010
01/07/2010
01/09/2010
01/11/2010
01/01/2011
01/03/2011
01/05/2011
01/07/2011
01/09/2011
01/11/2011
01/01/2012
01/03/2012
01/05/2012
01/07/2012
01/09/2012
01/11/2012
Aviation industry. It becomes an integral parts
of transportation planning. It sets targets and
goals for the airports, either for long term or
medium term planning. The primary statistical
methods used in airport aviation activity
forecasting are market share approach,
econometric modeling, and time series
modeling.
Model Used:
Based on a historical data of the airports, (3
years on monthly bases) the mathematical
model is developed where its fairness
an goodness of fit can be defined by two
important factors:
R
2
S. T (Signal Tracking) ..(- 4 < S.T. < 4)
There are many factors that may measure
the airport performance, mainly:
2) Aircraft Movement and
3) Freight
SANA’A Airport
Sana’a International Airport or El Rahaba
Airport (Sana’a International) (IATA: SAH,
ICAO: OYSN) is an international airport
located in Sana’a, the capital of Yemen.
Recently Yemen passes in a transition phase,
as results a democracy. This situation effects
on 2011 data base.
So the basic analysis addressing 2008,
2009, and 2010. And the forecasted period
are 2011 and 2012.
Passenger Forecasting 2012 = 2,048,088
Pax
Peak Periods: Jul =210,230 Aug =206,205
Annual Growth Rate: 3 %
The Model is good as R = 78%
Aircraft Movement Forecasting 2012 =
39,606
Peak Periods: Jul =3540 Aug =3361
Annual Growth: 16%.
The Model is fairly fitted as R = 94%
And reflects the recent data
Freights &Mails Forecasting 2012 = 23493
Tone. Peak Periods: May =2205 Tone.
Annual Growth: 2.4%.
The Model reflects a lot of discrepancies as
R=38% while its signal tracking = -3.02, so
results should take in caution.
yemen Airports
Aircraft Movement Forecasting 2012
Freights & Mails Forecasting 2012
Sana’a Airport (Seasonlity Model)

arab Airports
400,000
450,000
500,000
550,000
600,000
650,000
700,000
NoofPassengers
Sharjah Airport
Trafﬁc Forecasting 2012
Forecast
Actual
R2 = 89%
S.T.= -1.17
2012(F) = 6,863,141 PAX
TIME (Month)
01/01/2009
01/03/2009
01/05/2009
01/07/2009
01/09/2009
01/11/2009
01/01/2010
01/03/2010
01/05/2010
01/07/2010
01/09/2010
01/11/2010
01/01/2011
01/03/2011
01/05/2011
01/07/2011
01/09/2011
01/11/2011
01/01/2012
01/03/2012
01/05/2012
01/07/2012
01/09/2012
01/11/2012
650,000
700,000
750,000
800,000
850,000
900,000
950,000
NoofPassengers
Bahrain Airport
Traffic Forecasting 2011-2012
Forecast
Actual
R2 = 71%
S.T.= - 2.79
2012(F)= 9,287,978 Pax
TIME (Month)
01/01/2008
01/04/2008
01/07/2008
01/10/2008
01/01/2009
01/04/2009
01/10/2009
01/10/2009
01/01/2010
01/04/2010
01/07/2010
01/10/2010
01/01/2011
01/04/2011
01/07/2011
01/10/2011
01/01/2012
01/04/2012
01/07/2012
01/10/2012
Dubai International Airport
(IATA: DXB, ICAO: OMDB) is an international
airport serving Dubai. It is a major aviation hub
in the Middle East, and is the main airport of
Emirates States.
In 2011 DXB handled a record 50.98 million in
passenger traffic, a 8% increase over the 2010
fiscal year. This made it the 13th busiest airport in
the world by passenger traffic and the 4th busiest
airport in the world by international passenger
traffic.
Peak Periods: Jul = 5116686 Aug = 5109256
Annual Growth Rate: 10.5%
The Model is fairly good as R
2
= 89%.
Bahrain International Airport
(IATA: BAH, ICAO: OBBI) is an international
airport located in Muharraq, an island on the
northern tip of Bahrain, about 7 km (4.3 mi)
northeast of the capital Manama. It is the primary
hub for Gulf Air and Bahrain Air.
The airport has a three star rating from
Skytrax’s airport grading exercise. In 2010,
Bahrain Airport was named as the winner of
the Best Airport in the Middle East Award at the
Skytrax 2010 World Airport Awards.
Peak Periods: Jul = 903722Aug = 912338
The Model is fair as R
2
= 71%.
Sharjah International Airport
(IATA: SHJ, ICAO: OMSJ) is located in Sharjah,
United Arab Emirates. Sharjah Airport is the
second largest Middle East Airfreight Hub in
terms of cargo tonnage, according to official 2009
statistics from Airports Council International.
Ground services company, Sharjah Aviation
Services, handled 421,398 tonnes in 2009 - a
16.1% increase year on year.
Sharjah International Airport is home base of
the low-cost carrier Air Arabia.
2
= 89%.
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000
5,000,000
5,500,000
NoofPassengers
Dubia Airport
Trafﬁc Forecasting 2011-2012
Forecast
Actual
R2 = 89%
S.T.= 3.06
2012 (F) =56,277,296 Pax
TIME (Month)
01/01/2008
01/04/2008
01/07/2008
01/10/2008
01/01/2009
01/04/2009
01/10/2009
01/10/2009
01/01/2010
01/04/2010
01/07/2010
01/10/2010
01/01/2011
01/04/2011
01/07/2011
01/10/2011
01/01/2012
01/04/2012
01/07/2012
01/10/2012
Traffic Forecasting 2011 - 2012
Traffic Forecasting 2011 - 2012
Traffic Forecasting 2012
Dubai Airport (Seasonlity Model)
Bahrain Airport (Seasonlity Model)
Sharjah Airport (Seasonlity Model)

Hong Kong International Airport (HKIA)
(IATA: HKG, ICAO: VHHH) is the main airport in
Hong Kong. It is colloquially known as Chek Lap
Kok Airport. The airport opened for commercial
operations in 1998, replacing Kai Tak, and is
an important regional trans-shipment centre,
passenger hub and gateway for destinations in
Mainland China and the rest of Asia. Hong Kong
International Airport has won eight Skytrax World
Airport Awards for customer satisfaction in eleven
years. HKIA ranked second and third in 2009 and
2010 respectively for the Skytrax World Airport
Awards, and has also won the Skytrax World
Airport of the Year 2011.
Annual Growth: 6.4%
2
= 85%
3,000
3,500
4,000
4,500
5,000
5,500
NoofPassengers(1000)
HONG KONG Airport (Seasonlity Model)
Forecast
Actual
R2 = 85 %
S.T.= 2.43
2012(F) = 60,503,000 Pax
TIME (Month)
01/01/2009
01/03/2009
01/05/2009
01/07/2009
01/09/2009
01/11/2009
01/01/2010
01/03/2010
01/05/2010
01/07/2010
01/09/2010
01/11/2010
01/01/2011
01/03/2011
01/05/2011
01/07/2011
01/09/2011
01/11/2011
01/01/2012
01/03/2012
01/05/2012
01/07/2012
01/09/2012
01/11/2012
Amsterdam Airport Schiphol
(IATA: AMS, ICAO: EHAM) is the Netherlands’
main international airport, The airport is the
primary hub for KLM, Martinair, Transavia and
Arkefly. Schiphol is an important European
airport, ranking as Europe’s 4th busiest and
the world’s 12th busiest by total passenger
traffic. It also ranks as the world’s 6th busiest by
international passenger traffic and the world’s
17th largest for cargo tonnage. 45.3 million
passengers passed through the airport in 2010, a
4% increase compared with 2009.
Annual Growth: 6.1%
The Model is fair fitted as R2
= 96%2,500
3,000
3,500
4,000
4,500
5,000
5,500
(Seasonlity Model)
Forecast
Actual
R2 = 96 %
S.T.= -1.92
2012(F) = 51,989,842 Pax
TIME (Month)
01/01/2009
01/03/2009
01/05/2009
01/07/2009
01/09/2009
01/11/2009
01/01/2010
01/03/2010
01/05/2010
01/07/2010
01/09/2010
01/11/2010
01/01/2011
01/03/2011
01/05/2011
01/07/2011
01/09/2011
01/11/2011
01/01/2012
01/03/2012
01/05/2012
01/07/2012
01/09/2012
01/11/2012
Hartsfield–Jackson Atlanta International
Airport
(IATA: ATL, ICAO: KATL, FAA LID: ATL), known
locally as Atlanta Airport, Hartsfield Airport, and
Hartsfield–Jackson. It has been the world’s
busiest airport by passenger traffic and number
of landings and take-offs since 2005. Hartsfield–
Jackson held its ranking as the world’s busiest
airport in 2010, both in terms of passengers and
number of flights, by accommodating 89 million
passengers (243,000 passengers daily) and
950,119 flights.
Peak Periods: Jul = 9,028,647
Annual Growth: 2.2%
2
= 96%.
5,500
6,000
6,500
7,000
7,500
8,000
8,500
9,000
9,500
(Seasonlity Model)
Forecast
Actual
R2 = 96 %
S.T.= 0.00
2012(F) = 94,030,595 Pax
TIME (Month)
01/01/2009
01/03/2009
01/05/2009
01/07/2009
01/09/2009
01/11/2009
01/01/2010
01/03/2010
01/05/2010
01/07/2010
01/09/2010
01/11/2010
01/01/2011
01/03/2011
01/05/2011
01/07/2011
01/09/2011
01/11/2011
01/01/2012
01/03/2012
01/05/2012
01/07/2012
01/09/2012
01/11/2012
Atlanta Airport (Seasonlity Model)
Hong Kong Airport (Seasonlity Model)
Schiphol Airport (Seasonlity Model)

Mohammed Salem Awadh
Currently, he is a Consultant at Yemenia – Yemen
Airways, has an Executive - MBA, from a dual MBA
program form MSM and Sana’a University ( 2010), A
bachelor’s degree in Mechanical Engineering from
Aden University (1986), IATA Diploma in Airline
Management – 1996 (Geneva ), IATA Diploma in
Airline Marketing (distinction) -2006 (Geneva ), he
joined Yemenia in 1988, and hold many managerial
various positions among which; Head of reliability and
maintenance, projects and research manager, Acting a
Corporate Planning Director, Aden Regional Director
and finally Chairman Adviser . He served many Yemeni companies and airlines as a
scientific consultant in supply chain, forecasting and maintenance. Also he served as
member of the both the Arabic Strategic Team and Arabic Planning Committee of
AACO. Mohammed is a member of AGIFORS and ATRS.

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