| PSO-BP混合预测模型及在港口集装箱吞吐量预测中的应用 |
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| 引用本文： | 严武元,王少梅.PSO-BP混合预测模型及在港口集装箱吞吐量预测中的应用[J].武汉理工大学学报(交通科学与工程版),2007,31(3):525-528. |
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| 作者姓名： | 严武元 王少梅 |
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| 作者单位： | 武汉理工大学物流工程学院武汉430063 |
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| 摘 要： | 运用粒子群优化算法代替BP神经网络的初始寻优,再用BP算法对优化的网络权值参数进一步精确优化,从而建立基于粒子群优化的BP神经网络模型.运用该模型对某港口集装箱吞吐量进行预测.应用结果表明,该预测模型不仅能较好地拟合港口集装箱吞吐量的历史数据,同时对港口集装箱吞吐量的远期预测也具有较好的效果.
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| 关 键 词： | 粒子群优化算法(PSO) BP神经网络 集装箱 吞吐量 预测 |
| 修稿时间： | 2007-02-13 |
Application of BP Network Model Based on PSO for Prediction of Container Throughput |
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| Yan Wuyuan,Wang Shaomei.Application of BP Network Model Based on PSO for Prediction of Container Throughput[J].journal of wuhan university of technology(transportation science&engineering),2007,31(3):525-528. |
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| Authors: | Yan Wuyuan Wang Shaomei |
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| Institution: | School of Logistics Engineering, WUT, Wuhan 430063 |
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| Abstract: | A BP neural network model based on particle swarm optimizer(PSO) is proposed in this paper.The basic idea of this model is: Firstly PSO is used to optimize the BP neural network's initialized weights,an optimized result is got;then based on the optimized result,the BP neural network is used for further optimization.The model is used to predict the container throughput of a port.The result of prediction shows that the PSO-BP model not only can fit the history data smoothly,but also can get good prediction of long term container throughput of the port. |
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| Keywords: | particle swarm optimize(PSO) BP neural network container throughput prediction |
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