SlideShare a Scribd company logo
1 of 14
Department of Computer Science and Engineering
Hamdard University Bangladesh
All Types of Models
 A Model is a representation and abstraction of anything such as a
real system, a proposed system, a futuristic system design, an
entity, a phenomenon, or an idea.
Concepts of Models
Models
Mathematical Physical
Dynamic Static Dynamic Static
Non-linear Linear Nonlinear Linear
Unstable
(Constrained)
Stable Unstable
(Nonexistent)
StableUnstable
(Explosive)
Stable
Computer
Dynamic Static
Classifications of Models
 Mathematical Model: is the one in which symbols and logic constitute the
model. The symbolism used can be a language or a mathematical notation.
 A simulation model is built in terms of logic and mathematical equations
and is an abstract model.
 Physical Model: Physical model is a smaller or larger physical copy of an
object. The object being modeled may be small (for example, an atom) or large
(for example, the Solar System).
 A model of an airplane (scaled down), a model of the atom (scaled up), a
map, a globe, a model car are examples of physical (iconic) models.
Mathematical Vs. Physical Models
 Static Model: is the one which describes relationships that do not change with
respect to time.
 An architectural model of a house is a static physical model.
 An equation relating the lengths and weights on each side of a
playground variation is a static mathematical model.
 Static computer model which means fixed.
 Dynamic Model: is the one which describes time-varying
relationships.
 A wind tunnel is a dynamic physical model.
 The equations of motion of the planets around the sun constitute a
dynamic mathematical model of the solar system.
 Dynamic computer usually means capable of action and/or change.
Static Vs. Dynamic (Abstract /Physical/Computer) Models
 Analytical Model: is the one which is solved by using the deductive reasoning of
mathematical theory.
 A Linear Programming model, a Mixed Integer Linear Programming
model, a nonlinear optimization model are examples of analytical
models.
 Numerical Model: is the one which is solved by applying
computational procedures.
 Finding the roots of a nonlinear algebraic equation, f(x) = 0, using the
numerical model.
Analytical Vs. Numerical Mathematical Models
 Linear Model: is the one which describes relationships in linear
form.
 The equation 3x + 4z + 1=0 is a linear model.
 Nonlinear Model: is the one which describes relationships in
nonlinear form.
 The equation 2𝑥2 + 𝑦3—2=0 is a nonlinear model.
Linear Vs. Nonlinear Mathematical Models
 Stable Model: is the one which tends to return to its initial condition
after being disturbed.
 Like a simple pendulum.
 Unstable Model: is the one which may or may not come back to its
initial condition after being disturbed.
Stable Or Unstable Mathematical Models
 Steady-State Model: is the one whose behavior in one time period is
of the same nature as any other period.
 Transient Model: is the one whose behavior changes with respect to
time.
time
Transient Behavior Steady-State Behavior
Steady-state Or Transient Mathematical Models
state
 Descriptive Model: a system that represent a relationship but does not
indicate any course of action.
 The equation F (force) = M (mass) x A (acceleration) is a descriptive
model.
 All simulation models are descriptive models.
 Prescriptive or Normative Model: a system in that it prescribes the course
of action that the decision maker should take to achieve a defined objective.
 Decision analysis models are prescriptive.
Descriptive Vs. Prescriptive (Normative) Models
 If the regression model includes not only the current but
also the lagged (past) values of the explanatory variables
(the X’s) it is called a distributed-lag model.
 If the model includes one or more lagged values of the
dependent variable among its explanatory variables, it is
called an autoregressive model. This model is know as a
dynamic model.
Distributed-lag Model
Cobweb Model
 It is an economic model.
 In the model of supply and demand, the price adjusts so that the quantity
supplied and quantity demand are equal.
 The equilibrium is not always clear, so that some slopes are unstable.
Thats All !
Thanks for
listening...

More Related Content

What's hot

Chapter 3 mathematical modeling
Chapter 3 mathematical modelingChapter 3 mathematical modeling
Chapter 3 mathematical modeling
Bin Biny Bino
 
Deterministic vs stochastic
Deterministic vs stochasticDeterministic vs stochastic
Deterministic vs stochastic
sohail40
 

What's hot (20)

Unit 1 introduction to simulation
Unit 1 introduction to simulationUnit 1 introduction to simulation
Unit 1 introduction to simulation
 
Chapter 3 mathematical modeling
Chapter 3 mathematical modelingChapter 3 mathematical modeling
Chapter 3 mathematical modeling
 
Mathematical modeling
Mathematical modelingMathematical modeling
Mathematical modeling
 
Simulation & Modelling
Simulation & ModellingSimulation & Modelling
Simulation & Modelling
 
System Modeling & Simulation Introduction
System Modeling & Simulation  IntroductionSystem Modeling & Simulation  Introduction
System Modeling & Simulation Introduction
 
System modeling and simulation full notes by sushma shetty (www.vtulife.com)
System modeling and simulation full notes by sushma shetty (www.vtulife.com)System modeling and simulation full notes by sushma shetty (www.vtulife.com)
System modeling and simulation full notes by sushma shetty (www.vtulife.com)
 
Modelling simulation (1)
Modelling simulation (1)Modelling simulation (1)
Modelling simulation (1)
 
Simulation, Modeling, it’s application, advantage & disadvantage
Simulation, Modeling, it’s application, advantage  &  disadvantageSimulation, Modeling, it’s application, advantage  &  disadvantage
Simulation, Modeling, it’s application, advantage & disadvantage
 
Steepest descent method
Steepest descent methodSteepest descent method
Steepest descent method
 
Optimization problems and algorithms
Optimization problems and  algorithmsOptimization problems and  algorithms
Optimization problems and algorithms
 
Mathematical modelling ppt
Mathematical modelling pptMathematical modelling ppt
Mathematical modelling ppt
 
System Modelling
System ModellingSystem Modelling
System Modelling
 
continuous and discrets systems
continuous  and discrets systemscontinuous  and discrets systems
continuous and discrets systems
 
Simulation
SimulationSimulation
Simulation
 
Simulation
SimulationSimulation
Simulation
 
System dynamics ch 1
System dynamics ch 1System dynamics ch 1
System dynamics ch 1
 
Discrete event-simulation
Discrete event-simulationDiscrete event-simulation
Discrete event-simulation
 
Simulation
SimulationSimulation
Simulation
 
Introduction to System Dynamics
Introduction to System DynamicsIntroduction to System Dynamics
Introduction to System Dynamics
 
Deterministic vs stochastic
Deterministic vs stochasticDeterministic vs stochastic
Deterministic vs stochastic
 

Similar to All types of model(Simulation & Modelling) #ShareThisIfYouLike

Similar to All types of model(Simulation & Modelling) #ShareThisIfYouLike (20)

Models of Operations Research is addressed
Models of Operations Research is addressedModels of Operations Research is addressed
Models of Operations Research is addressed
 
Mathematical modeling
Mathematical modelingMathematical modeling
Mathematical modeling
 
Mc0079 computer based optimization methods--phpapp02
Mc0079 computer based optimization methods--phpapp02Mc0079 computer based optimization methods--phpapp02
Mc0079 computer based optimization methods--phpapp02
 
Matlab:Regression
Matlab:RegressionMatlab:Regression
Matlab:Regression
 
Matlab: Regression
Matlab: RegressionMatlab: Regression
Matlab: Regression
 
Master of Computer Application (MCA) – Semester 4 MC0079
Master of Computer Application (MCA) – Semester 4  MC0079Master of Computer Application (MCA) – Semester 4  MC0079
Master of Computer Application (MCA) – Semester 4 MC0079
 
McGraw Hill Simulation Modeling and Analysis
McGraw Hill  Simulation Modeling and AnalysisMcGraw Hill  Simulation Modeling and Analysis
McGraw Hill Simulation Modeling and Analysis
 
Introduction to mathematical modelling
Introduction to mathematical modellingIntroduction to mathematical modelling
Introduction to mathematical modelling
 
Data driven models and machine learning
Data driven models and machine learningData driven models and machine learning
Data driven models and machine learning
 
Mathematical models & water resource management
Mathematical models & water resource managementMathematical models & water resource management
Mathematical models & water resource management
 
General Linear Model | Statistics
General Linear Model | StatisticsGeneral Linear Model | Statistics
General Linear Model | Statistics
 
Mapa conceptual modelos matematicos asig#2
Mapa conceptual modelos matematicos  asig#2Mapa conceptual modelos matematicos  asig#2
Mapa conceptual modelos matematicos asig#2
 
Bengkel smartPLS 2011
Bengkel smartPLS 2011Bengkel smartPLS 2011
Bengkel smartPLS 2011
 
Modeling & Simulation Lecture Notes
Modeling & Simulation Lecture NotesModeling & Simulation Lecture Notes
Modeling & Simulation Lecture Notes
 
L1_Introduction.pdf
L1_Introduction.pdfL1_Introduction.pdf
L1_Introduction.pdf
 
Application of calculus in cse
Application of calculus in cseApplication of calculus in cse
Application of calculus in cse
 
Md simulation and stochastic simulation
Md simulation and stochastic simulationMd simulation and stochastic simulation
Md simulation and stochastic simulation
 
Structural Dynamic Reanalysis of Beam Elements Using Regression Method
Structural Dynamic Reanalysis of Beam Elements Using Regression MethodStructural Dynamic Reanalysis of Beam Elements Using Regression Method
Structural Dynamic Reanalysis of Beam Elements Using Regression Method
 
Operation research unit1 introduction and lpp graphical and simplex method
Operation research unit1 introduction and lpp graphical and simplex methodOperation research unit1 introduction and lpp graphical and simplex method
Operation research unit1 introduction and lpp graphical and simplex method
 
Lehmann 1990
Lehmann 1990Lehmann 1990
Lehmann 1990
 

More from United International University

Making Complex Decisions(Artificial Intelligence)
Making Complex Decisions(Artificial Intelligence)Making Complex Decisions(Artificial Intelligence)
Making Complex Decisions(Artificial Intelligence)
United International University
 

More from United International University (20)

Digital Devices (3rd chapter-2nd part)
Digital Devices (3rd chapter-2nd part)Digital Devices (3rd chapter-2nd part)
Digital Devices (3rd chapter-2nd part)
 
Network Topology (partial)
Network Topology (partial)Network Topology (partial)
Network Topology (partial)
 
Corona prediction from symptoms v1.4
Corona prediction from symptoms v1.4Corona prediction from symptoms v1.4
Corona prediction from symptoms v1.4
 
Introduction to Cloud Computing
Introduction to Cloud ComputingIntroduction to Cloud Computing
Introduction to Cloud Computing
 
ICT-Number system.সংখ্যা পদ্ধতি(৩য় অধ্যায়-১ম অংশ)
ICT-Number system.সংখ্যা পদ্ধতি(৩য় অধ্যায়-১ম অংশ)ICT-Number system.সংখ্যা পদ্ধতি(৩য় অধ্যায়-১ম অংশ)
ICT-Number system.সংখ্যা পদ্ধতি(৩য় অধ্যায়-১ম অংশ)
 
Wireshark Lab HTTP, DNS and ARP v7 solution
Wireshark Lab HTTP, DNS and ARP v7 solutionWireshark Lab HTTP, DNS and ARP v7 solution
Wireshark Lab HTTP, DNS and ARP v7 solution
 
Wireshark lab ssl v7 solution
Wireshark lab ssl v7 solutionWireshark lab ssl v7 solution
Wireshark lab ssl v7 solution
 
Network Security(MD5)
Network Security(MD5)Network Security(MD5)
Network Security(MD5)
 
Secure Electronic Transaction
Secure Electronic TransactionSecure Electronic Transaction
Secure Electronic Transaction
 
Oracle installation
Oracle installationOracle installation
Oracle installation
 
IEEE 802.11 Project
IEEE 802.11 ProjectIEEE 802.11 Project
IEEE 802.11 Project
 
SONET-Communication Engineering
SONET-Communication EngineeringSONET-Communication Engineering
SONET-Communication Engineering
 
Security Issues for Cellular Telephony
Security Issues for Cellular TelephonySecurity Issues for Cellular Telephony
Security Issues for Cellular Telephony
 
Type Checking(Compiler Design) #ShareThisIfYouLike
Type Checking(Compiler Design) #ShareThisIfYouLikeType Checking(Compiler Design) #ShareThisIfYouLike
Type Checking(Compiler Design) #ShareThisIfYouLike
 
System imolementation(Modern Systems Analysis and Design)
System imolementation(Modern Systems Analysis and Design)System imolementation(Modern Systems Analysis and Design)
System imolementation(Modern Systems Analysis and Design)
 
Making Complex Decisions(Artificial Intelligence)
Making Complex Decisions(Artificial Intelligence)Making Complex Decisions(Artificial Intelligence)
Making Complex Decisions(Artificial Intelligence)
 
Free Space Management, Efficiency & Performance, Recovery and NFS
Free Space Management, Efficiency & Performance, Recovery and NFSFree Space Management, Efficiency & Performance, Recovery and NFS
Free Space Management, Efficiency & Performance, Recovery and NFS
 
Overview of Computer Graphics
Overview of Computer GraphicsOverview of Computer Graphics
Overview of Computer Graphics
 
Keyboard & Mouse basics
Keyboard & Mouse basics Keyboard & Mouse basics
Keyboard & Mouse basics
 
Organization of a computer
Organization of a computerOrganization of a computer
Organization of a computer
 

Recently uploaded

Recently uploaded (20)

REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptx
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan Fellows
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)
 
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
 
HMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptx
HMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptxHMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptx
HMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptx
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...
 
Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...
Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...
Beyond_Borders_Understanding_Anime_and_Manga_Fandom_A_Comprehensive_Audience_...
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdf
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17
 
How to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptxHow to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptx
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
 
Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 

All types of model(Simulation & Modelling) #ShareThisIfYouLike

  • 1. Department of Computer Science and Engineering Hamdard University Bangladesh All Types of Models
  • 2.  A Model is a representation and abstraction of anything such as a real system, a proposed system, a futuristic system design, an entity, a phenomenon, or an idea. Concepts of Models
  • 3. Models Mathematical Physical Dynamic Static Dynamic Static Non-linear Linear Nonlinear Linear Unstable (Constrained) Stable Unstable (Nonexistent) StableUnstable (Explosive) Stable Computer Dynamic Static Classifications of Models
  • 4.  Mathematical Model: is the one in which symbols and logic constitute the model. The symbolism used can be a language or a mathematical notation.  A simulation model is built in terms of logic and mathematical equations and is an abstract model.  Physical Model: Physical model is a smaller or larger physical copy of an object. The object being modeled may be small (for example, an atom) or large (for example, the Solar System).  A model of an airplane (scaled down), a model of the atom (scaled up), a map, a globe, a model car are examples of physical (iconic) models. Mathematical Vs. Physical Models
  • 5.  Static Model: is the one which describes relationships that do not change with respect to time.  An architectural model of a house is a static physical model.  An equation relating the lengths and weights on each side of a playground variation is a static mathematical model.  Static computer model which means fixed.  Dynamic Model: is the one which describes time-varying relationships.  A wind tunnel is a dynamic physical model.  The equations of motion of the planets around the sun constitute a dynamic mathematical model of the solar system.  Dynamic computer usually means capable of action and/or change. Static Vs. Dynamic (Abstract /Physical/Computer) Models
  • 6.  Analytical Model: is the one which is solved by using the deductive reasoning of mathematical theory.  A Linear Programming model, a Mixed Integer Linear Programming model, a nonlinear optimization model are examples of analytical models.  Numerical Model: is the one which is solved by applying computational procedures.  Finding the roots of a nonlinear algebraic equation, f(x) = 0, using the numerical model. Analytical Vs. Numerical Mathematical Models
  • 7.  Linear Model: is the one which describes relationships in linear form.  The equation 3x + 4z + 1=0 is a linear model.  Nonlinear Model: is the one which describes relationships in nonlinear form.  The equation 2𝑥2 + 𝑦3—2=0 is a nonlinear model. Linear Vs. Nonlinear Mathematical Models
  • 8.  Stable Model: is the one which tends to return to its initial condition after being disturbed.  Like a simple pendulum.  Unstable Model: is the one which may or may not come back to its initial condition after being disturbed. Stable Or Unstable Mathematical Models
  • 9.  Steady-State Model: is the one whose behavior in one time period is of the same nature as any other period.  Transient Model: is the one whose behavior changes with respect to time. time Transient Behavior Steady-State Behavior Steady-state Or Transient Mathematical Models state
  • 10.  Descriptive Model: a system that represent a relationship but does not indicate any course of action.  The equation F (force) = M (mass) x A (acceleration) is a descriptive model.  All simulation models are descriptive models.  Prescriptive or Normative Model: a system in that it prescribes the course of action that the decision maker should take to achieve a defined objective.  Decision analysis models are prescriptive. Descriptive Vs. Prescriptive (Normative) Models
  • 11.
  • 12.  If the regression model includes not only the current but also the lagged (past) values of the explanatory variables (the X’s) it is called a distributed-lag model.  If the model includes one or more lagged values of the dependent variable among its explanatory variables, it is called an autoregressive model. This model is know as a dynamic model. Distributed-lag Model
  • 13. Cobweb Model  It is an economic model.  In the model of supply and demand, the price adjusts so that the quantity supplied and quantity demand are equal.  The equilibrium is not always clear, so that some slopes are unstable.
  • 14. Thats All ! Thanks for listening...