Nonlinear Identification of Ph Process using Support Vector Machine

This paper discusses the application of support vector machine in the area of identification of nonlinear dynamical systems. The aim of this paper is to identify suitable model structure for nonlinear dynamic system. In this paper, Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Support Vector Regression (SVR) models are applied for identification of highly nonlinear dynamic process. The results obtained by ANFIS and SVR are compared. The simulation results show that SVR is very effective to identify the nonlinear system.

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