The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Nov. 30, 1993
Filed:
Mar. 04, 1991
Ryuko Someya, Kawasaki, JP;
Michitaka Kosaka, Sagamihara, JP;
Hirotaka Mizuno, Ikeda, JP;
Toshiro Sasaki, Yokohama, JP;
Satoru Suemitsu, Kawasaki, JP;
Hitachi, Ltd., Tokyo, JP;
Abstract
A fuzzy evaluation and modification system evaluates and modifies the fuzzy knowledge in a fuzzy reasoning system. The fuzzy knowledge includes fuzzy rules, each described in an 'if . . . , then . . .' format, and membership functions defining meanings of propositions described in the 'if . . . , then' parts. Results of the fuzzy reasoning are monitored and compared with real data of a plurality of real test cases to evaluate the fuzzy knowledge. An influence power of each of the fuzzy rules with respect to the fuzzy reasoning results is attained for all the cases. Superpositional display of real data on the membership functions of the 'if . . .' part and reasoning results on the membership functions of the 'then . . .' part indicates a relationship between the membership function and the real data. The system includes units for obtaining a grade of rule representing adequacy of the fuzzy rule based on the membership functions associated with the 'if' part, attaining defuzzification values of the membership functions related to the 'then' part and obtaining differences between the defuzzification values and the real data. A relationship between the grade of rule and the difference thus obtained between the defuzzification values and the real data is outputted to an output unit. The fuzzy knowledge is modified by an operator in association with the output.