期刊
NEUROCOMPUTING
卷 302, 期 -, 页码 66-74出版社
ELSEVIER
DOI: 10.1016/j.neucom.2018.04.006
关键词
Neuro-fuzzy; ANFIS; Simulated annealing; System identification
资金
- Research Fund of Erciyes University of Turkey [FDK-2016-6371]
- Scientific and Technological Research Council of Turkey (TUBITAK) [2211-A]
In this paper, a new method is presented for the training of the Adaptive Neuro-Fuzzy Inference System (ANFIS). In this work, it is ensured that the best model is created by optimising the premise and consequent parameters of ANFIS by using Simulating Annealing (SA) based on an iterative algorithm. The proposed method was applied to dynamic system identification problems. The simulation results of the proposed method are compared with the Genetic algorithm (GA), Backpropagation (BP) algorithm and different methods from the literature. At the end of this study it was found that the optimisation of ANFIS parameters is more successful by using SA than by GA, BP and the other methods. (C) 2018 Elsevier B.V. All rights reserved.
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