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

被引：12

作者：

BIEN, ZG ^{[1
]}

CHUN, MG ^{[1
]}

机构：

[1] SAMSUNG ELECTR,CTR PROD ENGN,FACTORY AUTOMAT RES INST,SUWON 441742,SOUTH KOREA

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 1994年 / 2卷 / 02期

关键词：

INFERENCE NETWORK; RELATIONAL EQUATIONS; KNOWLEDGE REPRESENTATION; FORWARD AND BACKWARD REASONING;

D O I：

10.1109/91.277965

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：177 / 180

页数：4

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