DocumentCode :
303340
Title :
Learning in fuzzy neural networks
Author :
Feuring, Thomas
Author_Institution :
Inst. fur Inf., Westfalischen Wilhelms-Univ., Munster, Germany
Volume :
2
fYear :
1996
fDate :
3-6 Jun 1996
Firstpage :
1061
Abstract :
In our fuzzy neural networks, fuzzy weights and fuzzy operations are used for training crisp and fuzzy data. Theoretical studies of fuzzy networks where triangular fuzzy numbers are used, show that the output behaviour of these networks can be estimated for arbitrary input data. To make use of these properties we present two learning algorithms for our networks. We implemented and tested them and found our theoretical observations confirmed. The trained network has the capability of generalizing trained informations well
Keywords :
fuzzy neural nets; learning (artificial intelligence); crisp data; fuzzy data; fuzzy neural networks; fuzzy operations; fuzzy weights; learning algorithms; triangular fuzzy numbers; Backpropagation algorithms; Computer architecture; Computer networks; Fuzzy neural networks; Fuzzy sets; Intelligent networks; Learning systems; Multi-layer neural network; Neural networks; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1996., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3210-5
Type :
conf
DOI :
10.1109/ICNN.1996.549045
Filename :
549045
Link To Document :
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