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 |
A Generic Solving Method for FCSPs | 20 |
References | 28 |
Copyright | |
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Common terms and phrases
Adaptive algorithm application approach approximate reasoning Artificial Intelligence associated function attributes Baldwin J.F. behaviour causal classical CSPs classification cluster combination Cons(P constraint satisfaction Constraint Satisfaction Problems customer segmentation d₁ data browser database defined defuzzification diagnostic domain dynamic evidential logic rule evlog example fault FCSP Figure flexibility Fril fuzzy constraints fuzzy control Fuzzy Data Fuzzy Logic fuzzy relations fuzzy rules fuzzy set theory fuzzy subsets Fuzzy Systems global GUHA hypotheses IEEE implementation inference instantiation knowledge base LEVEL SP perturbation linguistic logic programming LogScale mass assignment membership functions method neural net Neural Networks neurofuzzy node null hypothesis operational amplifiers operators output parameters performed planning polytrees possibilistic possibility distribution Pr(C Pr(good predict prioritized constraints priority problem Proc quantifier represented rule base satisfies soft constraint strategy structure support pair symptoms uncertainty vectors vehicles Zadeh L.A. µF(ƒ