DocumentCode :
1976160
Title :
Multi-valued neural logic networks
Author :
Hsu, Loke-Soo ; Teh, Hoon-Heng ; Chan, Sing-Chai ; Loe, Kia Fock
Author_Institution :
Nat. Univ. of Singapore, Kent Ridge, Singapore
fYear :
1990
fDate :
23-25 May 1990
Firstpage :
426
Lastpage :
432
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
Keywords :
fuzzy logic; logic circuits; many-valued logics; neural nets; probability; decision-making; fuzzy network; multiple valued neural logic elements; probabilistic network; Joining processes; Multivalued logic; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multiple-Valued Logic, 1990., Proceedings of the Twentieth International Symposium on
Conference_Location :
Charlotte, NC
Print_ISBN :
0-8186-2046-3
Type :
conf
DOI :
10.1109/ISMVL.1990.122658
Filename :
122658
Link To Document :
بازگشت