Download - A presentation on fuzzy logic
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AAPRESENTATION PRESENTATION
ONONFUZZY LOGICFUZZY LOGIC
PREPARED BY:-PREPARED BY:-
PATEL SAHIL(06DME025)PATEL SAHIL(06DME025)
SAMA RIYAZ(06DME026)SAMA RIYAZ(06DME026)
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ARTIFICIAL INTELLIGENCE
“AI is the science of making machine do things that would require intelligence if done by man.”
The logic which we use to have fast response in a critical situations is fuzzy logic.
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Fuzzy Logic: What is it???
Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the concept of partial truth - truth values between "completely true" and "completely false"
It is a different way of looking at the world. It is a superset of Boolean logic! It deals with “shades of gray!”
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A Better Method to Deal Withthe Real World
Not just “True” and “False.” Takes on a range of values – True – Mostly True – Half True – Kind of True – False Values range from 0 to 1. – Including decimal values (0.2, 0.7, etc.)
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Fuzzy Logic Process
“Crisp” Input
“fuzzy” input
Fuzzification
Fuzzy logic
“Fuzzy” OutputDe-Fuzzification
“Crisp” Output
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Fuzzification
How tall is Kevin? Very Tall? Tall? Average? Short? Very Short?
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How tall is Kevin?
Very Tall (7 feet)? Tall (6 feet)? Average (5 feet)? Short (4 feet)? Very Short (3 feet)?
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Some examplesSome examples
If you are 5 feet: Very tall - 0% - Very Tall (7 feet)? Tall - 0% - Tall (6 feet)? Average 100% -Average (5 feet)? Short - 0% - Short (4 feet)? Very Short - 0% - Very Short (3 feet)?
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If you are If you are 5½ feet:5½ feet: Very tall - 0%Very tall - 0% -Very Tall (7 feet)?-Very Tall (7 feet)? Tall - Tall - 50%50% --Tall (6 feet)?Tall (6 feet)? Average - Average - 50%50% --Average (5 feet)?Average (5 feet)? Short - 0%Short - 0% -Short (4 feet)?-Short (4 feet)? Very Short - 0%Very Short - 0% -Very Short (3 feet)?-Very Short (3 feet)?
Not in boolean logicNot in boolean logic
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De-Fuzzification Two Methods:-1) Winner Take All
-Output “Hard Right” = 70%- It is the winner!- Output = 100 (from output mapping)- Looses some of the smoothness of fuzzy logic.
2) Weighted Average - Output “Hard Right” = 70% - Output “Left” = 20% - Output = 73.3
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Benefits of Fuzzy System Modeling
Ability to Model Highly Complex Business Problems Ability to Model System Involving Multiple Experts Reduce Model Complexity Improve Handling of Uncertain and Possibilities
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Common Objections to Fuzzy Logic
Much of the opposition to fuzzy logic is based on the misconception
Fuzzy logic invites the belief that the modeling process generates imprecise answers
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Applications
ABS Brakes Expert Systems Control Units Bullet train between Tokyo and Osaka Video Cameras Automatic Transmissions
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Conclusion
The exact directions and extent of future developments will be dictated by advancing technology and market forces
Fuzzy logic is a tool and can only useful and powerful when combined with Analytical Methodologies and Machine Reasoning Techniques
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Any Question?????
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Thank you