2. Outline
• Overview
• Early applications
• Example
• Logical analysis
• Fuzzy databases
• Comparison to probability
• Relation to ecorithms
3. Overview
• Term “Fuzzy Logic” coined in 1965 by Lotfi A. Zadeh.
• Deals with reasoning that is approximate rather than
fixed and exact.
• Form of may-valued logic.
• Variables may have values ranging between 0 &1.
• For example temperature values may be Cold, Warm
and Hot.
4. Early Applications
• Japanese were the first to utilize fuzzy
logic for practical applications.
• High-speed train in Sendai.
• Recognition of hand written symbols in
Sony pocket computers.
• Canon & Omron auto-focus & auto-aiming
cameras.
• Earthquake prediction and modeling
5. Example
• Fuzzy set theory defines fuzzy operators on fuzzy sets.
• But these operators may not be known.
• For this reason IF-THEN rules are used.
• E.g. simple temperature regulator that uses a fan might look like
this:
IF temperature IS very cold THEN stop fan
IF temperature IS cold THEN turn down fan
IF temperature IS normal THEN maintain level
IF temperature IS hot THEN speed up fan
• AND, OR, and NOT operators of Boolean logic also used.
• They are called the Zadeh operators.
7. Fuzzy Databases
• Once fuzzy relations are defined, it is possible to develop
fuzzy relational databases.
• First fuzzy relational database – FRDB in Maria
Zemankova's dissertation.
• Other model:
– Buckles-Petry model
– the Prade-Testemale Model
– the Umano-Fukami model or the GEFRED model.
• Fuzzy querying languages like SQLf by P. Bosc et al.
and the FSQL by J. Galindo et al.
8. Comparison to Probability
• concept of fuzzy
set membership i.e. how
much a variable is in a set
• concept of subjective
probability i.e., how
probable do I think that a
variable is in a set
Both are different ways of expressing uncertainty.
ProbabilityFuzzy Logic
