摘要
改进标准粒子群优化算法(PSO)的惯性权重参数,提出基于IPSO的BP神经网络算法,以提高物流配送中心选址的预测精度。仿真结果表明,IPSO-BP神经网络算法的预测精度优于常规BP神经网络算法,不仅改进了网络的收敛速度并且提高了预测准确性。
The BP neural network based on the improved particles warm optimization（IPSO） was proposed in this paper to improve the prediction accuracy of the distribution center location selection.The simulation results shown that prediction accuracy of the IPSO-BP neural network algorithm was better than that of conventional BP neural network algorithm.IPSO-BP neural network algorithm improved not only the convergence speed of the network but also the prediction accuracy.
出处
《广西科学院学报》
2012年第1期4-6,共3页
Journal of Guangxi Academy of Sciences
