DocumentCode
2879916
Title
Fuzzy neural logic network and its learning algorithms
Author
Chan, Sing-Chai ; Nah, Fui-Hoon
Author_Institution
Dept. of Inf. Syst. & Comput. Sci., Nat. Univ. of Singapore, Singapore
Volume
i
fYear
1991
fDate
8-11 Jan 1991
Firstpage
476
Abstract
The paper introduces the basic features of fuzzy neural logic network. Each fuzzy neural logic network model is trained from a set of knowledge in the form of examples using one of the three learning algorithms introduced. These three learning algorithms are the delta rule controlled learning algorithm and two mathematical construction algorithms, namely, the local learning method and the global learning method. Once the fuzzy neural logic network model is constructed, it is ready to accept any unknown input from the user. With a low percentage of mismatched features, output solution can be obtained
Keywords
fuzzy logic; knowledge acquisition; learning systems; neural nets; delta rule controlled learning algorithm; fuzzy neural logic network model; global learning; learning algorithms; learning by construction; local learning; mathematical construction algorithms; propagation rule; Computer science; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Humans; Information systems; Learning systems; Mathematical model; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 1991. Proceedings of the Twenty-Fourth Annual Hawaii International Conference on
Conference_Location
Kauai, HI
Type
conf
DOI
10.1109/HICSS.1991.183918
Filename
183918
Link To Document