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Prediction and optimization model of activated carbon double layer capacitors based on improved heuristic approach genetic algorithm neural network

Zhen Yang (Department of Chemical Engineering, East China University of Science and Technology, Shanghai, China)
Yun Lin (Department of Chemical Engineering, East China University of Science and Technology, Shanghai, China)
Xingsheng Gu (Information Science Institute, East China University of Science and Technology, Shanghai, China)
Xiaoyi Liang (Department of Chemical Engineering, East China University of Science and Technology, Shanghai, China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 10 July 2018

Issue publication date: 23 July 2018

150

Abstract

Purpose

The purpose of this paper is to study the electrochemical properties of electrode material on activated carbon double layer capacitors. It also tries to develop a prediction model to evaluate pore size value.

Design/methodology/approach

Back-propagation neural network (BPNN) prediction model is used to evaluate pore size value. Also, an improved heuristic approach genetic algorithm (HAGA) is used to search for the optimal relationship between process parameters and electrochemical properties.

Findings

A three-layer ANN is found to be optimum with the architecture of three and six neurons in the first and second hidden layer and one neuron in output layer. The simulation results show that the optimized design model based on HAGA can get the suitable process parameters.

Originality/value

HAGA BPNN is proved to be a practical and efficient way for acquiring information and providing optimal parameters about the activated carbon double layer capacitor electrode material.

Keywords

Acknowledgements

This work is partly supported by National Natural Science Foundation of China (21177038), China Scholarship Council Fund (201406745031) and Material Informatics for Engineering Design Research Group of Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA. The authors would like to thank and the anonymous reviewers for their constructive suggestions that have improved the quality of this work.

Citation

Yang, Z., Lin, Y., Gu, X. and Liang, X. (2018), "Prediction and optimization model of activated carbon double layer capacitors based on improved heuristic approach genetic algorithm neural network", Engineering Computations, Vol. 35 No. 4, pp. 1625-1638. https://doi.org/10.1108/EC-03-2017-0105

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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