Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/99561
Title: Multi-valued neural logic networks
Authors: Hsu, Loke-Soo 
Teh, Hoon-Heng 
Chan, Sing-Chai 
Kia, Fock Loe 
Issue Date: 1990
Citation: Hsu, Loke-Soo,Teh, Hoon-Heng,Chan, Sing-Chai,Kia, Fock Loe (1990). Multi-valued neural logic networks. Proceedings of The International Symposium on Multiple-Valued Logic : 426-432. ScholarBank@NUS Repository.
Abstract: Two types of networks that are useful in developing expert systems are proposed. The probabilistic network can be used for predictive types of expert systems, whereas the fuzzy network is more suitable for expert systems that help in decision making. In both cases, the expert system can operate in two modes. In the normal mode, rules are given by experts and weights are assigned values. In the learning mode, weights are allowed to vary while the system is fed with examples.
Source Title: Proceedings of The International Symposium on Multiple-Valued Logic
URI: http://scholarbank.nus.edu.sg/handle/10635/99561
ISSN: 0195623X
Appears in Collections:Staff Publications

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