GA-Based RBF Neural Network for Nonlinear SISO System

Jili Tao (), Ridong Zhang () and Yong Zhu ()
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Jili Tao: NingboTech University, School of Information Science and Engineering
Ridong Zhang: Hangzhou Dianzi University, The Belt and Road Information Research Institute
Yong Zhu: NingboTech University, School of Information Science and Engineering

Chapter Chapter 6 in DNA Computing Based Genetic Algorithm, 2020, pp 119-166 from Springer

Abstract: 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.

Date: 2020
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DOI: 10.1007/978-981-15-5403-2_6

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