Title :
Selection of the optimum number of hidden layers in neuro-fuzzy GMDH
Author :
Ichihashi, H. ; Harada, N. ; Nagasaka, K.
Author_Institution :
Coll. of Eng., Osaka Prefectural Univ., Sakai, Japan
Abstract :
An adaptive learning network (ALN) of group method of data handling (GMDH) type with error backpropagation is proposed, in which Gaussian radial basis functions (RBF) networks are applied to the partial descriptions of the GMDH. Optimum number of hidden layers in the ALN is selected applying the differential minimum bias criterion (DMC) and the Akaike´s information criterion. The validity of these two criteria are confirmed with the cross validation technique and the average mean log-likelihood
Keywords :
adaptive systems; feedforward neural nets; fuzzy logic; identification; information theory; learning systems; maximum likelihood estimation; Akaike´s information criterion; Gaussian radial basis functions networks; adaptive learning network; average mean log-likelihood; cross validation; differential minimum bias criterion; group method of data handling; neuro-fuzzy GMDH; optimum number selection; Adaptive systems; Backpropagation; Educational institutions; Fuzzy neural networks; Industrial engineering; Input variables; Intelligent networks; Maximum likelihood estimation; Nonlinear systems; Parameter estimation;
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
DOI :
10.1109/FUZZY.1995.409880
