Title :
Constructive algorithm for neuro-fuzzy networks
Author :
Mascioli, F. M Frattale ; Varazi, G.M. ; Martinelli, G. M M
Author_Institution :
INFO-COm Dept., Rome Univ., Italy
Abstract :
A constructive algorithm is proposed by merging the min-max and the ANFIS models in order to obtain neuro-fuzzy networks. The min-max model is used to determine an optimal set of IF-THEN rules by following a constructive procedure. By means of this set, the architecture of an ANFIS-like net is derived with good performances in terms of structural complexity, generalization capability and speed of convergence. Simulations are described to show the behavior of the proposed algorithm
Keywords :
convergence; fuzzy neural nets; minimax techniques; neural net architecture; ANFIS model; IF-THEN rules; convergence; generalization capability; min-max model; neuro-fuzzy networks; optimal rule set; structural complexity; Computational efficiency; Computational modeling; Computer architecture; Computer networks; Costs; Fuzzy logic; Fuzzy neural networks; Merging; Robustness; Uncertainty;
Conference_Titel :
Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7803-3796-4
DOI :
10.1109/FUZZY.1997.616411
