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Publikācija: Adaptive Learning Algorithm for Hybrid Fuzzy System

Publication Type Full-text conference paper published in other conference proceedings
Funding for basic activity Unknown
Defending: ,
Publication language English (en)
Title in original language Adaptive Learning Algorithm for Hybrid Fuzzy System
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Aleksandrs Vališevskis
Keywords adaptive learning algorithms, adaptive network, Adaptive Network Based Fuzzy Inference System, neuro-fuzzy systems, Resilient backpropagation
Abstract In this paper the possibility of improving convergence time of algorithms intended for tuning parameters of fuzzy system with inference mechanism realized with the help of adaptive network is considered. A new algorithm is proposed, which allows to decrease the number of iterations during learning process and to substantially decrease the number of computational operations that have to be performed during single iteration. Furthermore, analytical data is presented and it’s shown how to reduce the computational load in the case if the proposed algorithm is being used.
Reference Vališevskis, A. Adaptive Learning Algorithm for Hybrid Fuzzy System. In: Proceedings of the International Conference "Traditional and Innovations in Sustainable Development of Society", Latvia, Rēzekne, 28 Feb-2 Mar., 2002. Rēzekne: Rēzeknes Augstskola, 2002, pp.281-287.
ID 11126