Fuzzy And Evidence Reasoning
This volume gives readers a complete picture of fuzzy approximate reasoning and uncertainty reasoning based on evidence theory. The topics are systematically treated from fundamentals to advanced issues. Numerous examples illustrate the concepts.
The work decribes and analyzes various approaches regarding fuzzy approximate reasoning including fuzzy logics, uncertainty representation, and fuzzy inference patterns. Approximate reasoning based on evidence theory is mainly resulted from the authors' own research work.
The book can be used as a textbook for courses in uncertainty reasoning as well as a quick reference on techniques for managing uncertainty for any one working in the areas of expert systems.
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FUZZY SETS AND POSSIBILITY THEORY
KNOWLEDGE REPRESENTATION FUZZY TRUTH SPACE
COMPOSITIONAL RULES OF INFERENCE
7 other sections not shown
According approximate reasoning Assume Axiom backward inference basic probability assignment belief and plausibility belief function belief interval bL,b calculated Cartesian product chapter composition operator compositional rule computation concept confidence measure conjunction corresponding probability mass defined definition Dempster-Shafer theory Dempster's rule denote discussed disjunction Equation evidence theory Example expert systems false focal elements formula frame of discernment fuzzy inference fuzzy logic fuzzy quantifier fuzzy reasoning fuzzy relation fuzzy subset idle speed implication operator inference patterns inference procedures Let us consider linguistic variable maximally dependent assumption membership function min(l modus ponens modus tollens multivalued logic mutually exclusive assumption negation obtained plausibility measures possibility distribution Prade probability assignment function probability restriction problem proposition represents restriction on v(p rule of combination rule of inference semantic Sets and Systems summation tall truth table truth value uncertainty unit interval X2 is A2 Zadeh
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