Fuzzy LogicJames Frederick Baldwin The rapid growth of data and information confronting many in industry and business has created a need for extracting knowledge out of such data. Fuzzy logic is one of the techniques used within this area of computational and statistical tools. It has been a major commercial success, with many real-world applications including industrial control, medical and financial applications, and incorporation into consumer goods. Fuzzy sets generalise data and enable knowledge to be expressed as linguistic rules, giving a powerful and robust framework. This book discusses many existing applications and outlines the direction of future developments in fuzzy logic. |
Contents
Handling Priority and Preference in Constraint Satisfaction | 5 |
55 | 28 |
References | 75 |
Copyright | |
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Common terms and phrases
Adaptive algorithm application approach approximate reasoning Artificial Intelligence attributes Baldwin J.F. behaviour causal classification cluster combination Constraint Satisfaction Problems D₁ database defined defuzzification degree diagnostic diagnostic reasoning domain dynamic error evidential logic rule evlog example fault FCSP Figure flexibility Fril fuzzy constraints fuzzy control Fuzzy Data Browser Fuzzy Logic fuzzy relations fuzzy rules fuzzy set theory fuzzy subsets Fuzzy Systems global GUHA IEEE implementation inference instantiation Intelligent least prejudiced LEVEL SP perturbation linguistic Log Disp logic programming LogScale Martin T.P. mass assignment membership functions method neural net Neural Networks neurofuzzy node operational amplifiers operator output parameters performed planning point value polytrees possibilistic possibility distribution Pr(good predicting prioritized constraints priority problem Proc quantifier represented satisfies soft constraint solution strategy structure support pair symptoms tree tuple uncertainty vectors vehicles Zadeh L.A. µE(e µF(ƒ