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AN INFERENCE NETWORK FOR BIDIRECTIONAL APPROXIMATE REASONING BASED ON AN EQUALITY MEASURE

Author(s)
Bien, ZeungnamCHUN, MG
Issued Date
1994-05
DOI
10.1109/91.277965
URI
https://scholarworks.unist.ac.kr/handle/201301/9178
Fulltext
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0028438837
Citation
IEEE TRANSACTIONS ON FUZZY SYSTEMS, v.2, no.2, pp.177 - 180
Abstract
An inference network is proposed as a tool for bidirectional approximate reasoning. The inference network can be designed directly from the given fuzzy data (knowledge). If a fuzzy input is given for the inference network, then the network renders a reasonable fuzzy output after performing approximate reasoning based on an equality measure. Conversely, due to the bidirectional structure, the network can yield its corresponding reasonable fuzzy input for a given fuzzy output. This property makes it possible to perform forward and backward reasoning in the knowledge base system
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
ISSN
1063-6706

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