Title :
Backpropagation and genetic algorithms for training fuzzy neural nets
Author :
Buckley, James J. ; Reilly, Kevin D. ; Penmetcha, Krishnamraju V.
Author_Institution :
Dept. of Math., Alabama Univ., Birmingham, AL, USA
Abstract :
This paper concerns combined backpropagation and genetic training of fuzzy neural nets whose weights and signals are given as real or triangular fuzzy numbers. The proposed fuzzy neural network with backpropagation and genetic-based learning system is used on problems which map a fuzzy or real input to a fuzzy or real output based on interval arithmetic operations. Experimental results demonstrating characteristics of various nonlinear mappings are discussed
Keywords :
backpropagation; fuzzy neural nets; fuzzy set theory; genetic algorithms; learning systems; backpropagation; fuzzy neural nets; genetic algorithms; learning system; nonlinear mappings; real fuzzy numbers; triangular fuzzy numbers; Arithmetic; Backpropagation; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mathematics; Neural networks; Neurons; Transfer functions;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.551710
