Self-organizing interval type-2 fuzzy neural network based on singular value decomposition and QR decomposition
Panchao Wang, Taoyan Zhao · 2023
In this paper, a self-organizing interval type-2 fuzzy neural network based on singular value decomposition and QR decomposition with column pivoting (SVD-QR)method is proposed to solve the identification problem of nonlinear systems. The network model can realize both structure learning and parameter learning. Firstly, in the aspect of structure learning, error criterion and completeness criterion of fuzzy rules are used to judge whether the rules are growing or not, and at the same time, SVD-QR method is used to find the less active rules to delete. Secondly, a sliding-window secondorder algorithm with forgetting factor is used to optimize the parameters. Finally, the proposed model is applied to one typical nonlinear examples for identification. The experimental result shows that the proposed model can produce a relatively compact network structure and has the high identification and the forecast precision.