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GA-Based RBF Neural Network for Nonlinear SISO System

  • Jili TaoEmail author
  • Ridong Zhang
  • Yong Zhu
Chapter
  • 35 Downloads

Abstract

Radial basis function (RBF) neural network is efficient to model nonlinear systems with its simpler network structure and faster learning capability. The temperature and pressure modeling of the coke furnace in an industrial coke equipment is not very easy due to disturbances, nonlinearity, and switches of coke towers. To construct the temperature and pressure models in a coke furnace, RBF neural network is utilized to improve the modeling precision. Moreover, the shortcoming of RBF neural network, such as over-fitting is overcome.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Information Science and EngineeringNingboTech UniversityNingboChina
  2. 2.The Belt and Road Information Research InstituteHangzhou Dianzi UniversityHangzhouChina

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