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  • 标题:Two Kinds of Classifications Based on Improved Gravitational Search Algorithm and Particle Swarm Optimization Algorithm
  • 本地全文:下载
  • 作者:Hongping Hu ; Xiaxia Cui ; Yanping Bai
  • 期刊名称:Advances in Mathematical Physics
  • 印刷版ISSN:1687-9120
  • 电子版ISSN:1687-9139
  • 出版年度:2017
  • 卷号:2017
  • DOI:10.1155/2017/2131862
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Gravitational Search Algorithm (GSA) is a widely used metaheuristic algorithm. Although fewer parameters in GSA were adjusted, GSA has a slow convergence rate. In this paper, we change the constant acceleration coefficients to be the exponential function on the basis of combination of GSA and PSO (PSO-GSA) and propose an improved PSO-GSA algorithm (written as I-PSO-GSA) for solving two kinds of classifications: surface water quality and the moving direction of robots. I-PSO-GSA is employed to optimize weights and biases of backpropagation (BP) neural network. The experimental results show that, being compared with combination of PSO and GSA (PSO-GSA), single PSO, and single GSA for optimizing the parameters of BP neural network, I-PSO-GSA outperforms PSO-GSA, PSO, and GSA and has better classification accuracy for these two actual problems.
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