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Information Journal Paper

Title

A TS FUZZY MODEL DERIVED FROM A TYPICAL MULTI-LAYER PERCEPTRON

Pages

  1-21

Abstract

 In this paper, we introduce a Takagi-Sugeno (TS) fuzzy model which is derived from a typical Multi-Layer Perceptron Neural Network (MLP NN). At first, it is shown that the considered MLP NN can be interpreted as a variety of TS fuzzy model. It is discussed that the utilized Membership Function (MF) in such TS fuzzy model, despite its flexible structure, has some major restrictions. After modifying the MF, we introduce a TS fuzzy model whose MFs are tunable near and far from focal points, separately. To identify such TS fuzzy model, an incremental learning algorithm, based on an efficient space partitioning technique, is proposed. Through an illustrative example, the methodology of the learning algorithm is explained. Next, through two case studies: approximation of a nonlinear function for a sun sensor and identification of a PH NEUTRALIZATION PROCESS, the superiority of the introduced TS fuzzy model in comparison to some other TS fuzzy models and MLP NN is shown.

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    APA: Copy

    KALHOR, A., ARRABI, B.N., LUCAS, C., & TARVIRDIZADEH, B.. (2015). A TS FUZZY MODEL DERIVED FROM A TYPICAL MULTI-LAYER PERCEPTRON. IRANIAN JOURNAL OF FUZZY SYSTEMS, 12(2), 1-21. SID. https://sid.ir/paper/690804/en

    Vancouver: Copy

    KALHOR A., ARRABI B.N., LUCAS C., TARVIRDIZADEH B.. A TS FUZZY MODEL DERIVED FROM A TYPICAL MULTI-LAYER PERCEPTRON. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2015;12(2):1-21. Available from: https://sid.ir/paper/690804/en

    IEEE: Copy

    A. KALHOR, B.N. ARRABI, C. LUCAS, and B. TARVIRDIZADEH, “A TS FUZZY MODEL DERIVED FROM A TYPICAL MULTI-LAYER PERCEPTRON,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 12, no. 2, pp. 1–21, 2015, [Online]. Available: https://sid.ir/paper/690804/en

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