Knowledge representation and acquisition in expert systems for pattern recognition
O. M. Vasil’ev, Dmitry Vetrov, Dmitry Kropotov · Computational Mathematics and Mathematical Physics · 2007
A new approach to the design of fuzzy expert systems is proposed. The representation of knowledge and the formation of statements by fuzzy logic tools are discussed in detail. A model of fuzzy inference is described. Primary attention is given to automatic extraction of knowledge (fuzzy inference rules) from a set of precedents. Various performance criteria for rules are introduced, and an algorithm for their generation (the method of effective restrictions) is proposed. An extension of the type of admissible rules by introducing a fuzzy disjunction operation is described. The possibility of optimizing the rules found is explored. The benefits of the approaches proposed are illustrated by experiments.