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Gu, J., Yin, G.H., Huang, P.F., Guo, J.L. and Chen, L.J. (2017) An Improved Back Propagation Neural Network Prediction Model for Subsurface Drip Irrigation System. Computers & Electrical Engineering, 60, 58-65. https://doi.org/10.1016/j.compeleceng.2017.02.016

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• TITLE: Application of Artificial Electric Field Algorithm in Function Optimization

  AUTHORS: Peizhen Xu, Jiatang Cheng

  KEYWORDS: Artificial Electric Field Algorithm, Optimization, Benchmark Function, Neural Network

  JOURNAL NAME: Open Access Library Journal, Vol.9 No.10, October 24, 2022

  ABSTRACT: Artificial electric field (AEF) algorithm is a newly developed heuristic intelligent optimization method, which has the advantages of simple implementation process and less control parameters. So far, it has been applied in some engineering and scientific research fields. For these reasons, AEF algorithm is used to address six benchmark functions to evaluate its search ability. After that, AEF algorithm is combined with BP neural network to find the optimal initial weights and biases, and then the optimized BP network is employed to fit a multi-input single-output nonlinear function. Experimental results indicate that AEF algorithm has good convergence performance and robustness.