A New Decision-Making GMDH Neural Network: Effective for Limited and Fuzzy Data.

Journal: Computational intelligence and neuroscience
Published Date: Oct 14, 2022

Abstract

This paper presents a new approach to solve multi-objective decision-making (DM) problems based on neural networks (NN). The utility evaluation function is estimated using the proposed group method of data handling (GMDH) NN. A series of training data is obtained based on a limited number of initial solutions to train the NN. The NN parameters are adjusted based on the error propagation training method and unscented Kalman filter (UKF). The designed DM is used in solving the practical problem, showing that the proposed method is very effective and gives favorable results, under limited fuzzy data. Also, the results of the proposed method are compared with some similar methods.

Authors

  • Xiaofeng Hong
    Zhejiang Guangsha Vocational and Technical University of Construction, Dongyang 322100, China.
  • Yonghui Zhao
    Zhejiang Guangsha Vocational and Technical University of Construction, Dongyang 322100, China.
  • Nasreen Kausar
    Department of Mathematics, Faculty of Arts and Science, Yildiz Technical University, Esenler, Istanbul 34210, Turkey.
  • Ardashir Mohammadzadeh
    Control Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran. Electronic address: a.mohammadzadeh@tabrizu.ac.ir.
  • Dragan Pamučar
    Department of Logistics, University of Defence in Belgrade, Pavla Jurisica Sturma 33, 11000 Belgrade, Serbia.
  • Nasr Al Din Ide
    Department of Mathematics, University of Aleppo, Aleppo, Syria.

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