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On the use of interval mathematics in fuzzy expert systems
Author(s) -
Wagman Daniel,
Schneider Moti,
Shnaider Eliahu
Publication year - 1994
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550090205
Subject(s) - backward chaining , expert system , computer science , preprocessor , inference , matching (statistics) , modus ponens , fuzzy logic , artificial intelligence , premise , rule of inference , inference engine , mathematics , linguistics , statistics , philosophy
Fuzzy expert systems attempt to model the cognitive processes of human experts. They currently accomplish this by capturing knowledge in the form of linguistic propositions. Real‐world problems dictate the need to include mathematical knowledge as well. Pattern matching is a critical part of the inference procedure in expert systems. Matches are made between data clauses, premise clauses, and conclusion clauses, forming an inference chain. Preprocessing the clauses may generate intervals of real numbers which are compared in the fuzzy matching algorithm. These same intervals may be used in arithmetic expressions. the purpose of this article is to devise a method for incorporating arithmetic expressions into inference process of Fuzzy Expert Systems. Interval arithmetic is used to evaluate these expressions. Logical relations between intervals are analyzed using probability theory. © 1994 John Wiley & Sons, Inc.