An approximate analogical reasoning approach based on similarity measures

An approximate analogical reasoning schema (AARS) which exhibits the advantages of fuzzy set theory and analogical reasoning in expert systems development is described. The AARS avoids going through the conceptually complicated compositional rule of inference. It uses a similarity measure of fuzzy sets as well as a threshold to determine whether a rule should be fired and a modification function inferred from a similarity measure to deduce a consequent. Some numerical examples to illustrate the operation of the schema are presented. Finally, the proposed schema is compared with conventional expert systems and existing fuzzy expert systems