TY - GEN
T1 - Fuzzy neural logic network and its learning algorithms
AU - Chan, Sing-Chai
AU - Nah, Fui-Hoon
PY - 1991/1
Y1 - 1991/1
N2 - This 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.
AB - This 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.
UR - http://www.scopus.com/inward/record.url?scp=84886253414&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84886253414&origin=recordpage
U2 - 10.1109/HICSS.1991.183918
DO - 10.1109/HICSS.1991.183918
M3 - 32_Refereed conference paper (with ISBN/ISSN)
SN - 9780818621215
VL - 1
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 476
EP - 485
BT - Proceedings of the Twenty-Fourth Annual Hawaii International Conference on System Sciences
PB - IEEE
T2 - 24th Annual Hawaii International Conference on System Sciences (HICSS 1991)
Y2 - 8 January 1991 through 11 January 1991
ER -