Author(s)

Peizhen Xu, Jiatang Cheng^*

The College of Mechanical and Control Engineering, Guilin University of Technology, Guilin, China.

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.

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

Xu, P.Z. and Cheng, J.T. (2022) Application of Artificial Electric Field Algorithm in Function Optimization. Open Access Library Journal, 9, 1-7. doi: 10.4236/oalib.1109377.