| 基于PSO-BP算法的运输组织精益生产评价 |
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| 引用本文： | 钱武生.基于PSO-BP算法的运输组织精益生产评价[J].兰州铁道学院学报,2007,26(4):29-31,39. |
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| 作者姓名： | 钱武生 |
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| 作者单位： | 乌鲁木齐铁路局奎屯车务段 新疆奎屯833200 |
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| 摘 要： | 在构建车站运输组织精益生产评价系统的基础上,建立用粒子群优化算法(PSO)和BP神经网络相结合的混合算法来进行综合评价的模型.该模型全面考虑影响运输组织生产的各种因素,将定性分析和定量分析相结合,使评价结果更符合实际、更可靠.实例计算结果表明:PSO-BP方法简便、通用,其结果符合生产实际,能很好的反应运输组织精益生产的实施效果.
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| 关 键 词： | 铁路车站运输组织 精益生产 BP神经网络 粒子群优化算法 |
| 文章编号： | 1001-4373（2007）04-0029-03 |
| 修稿时间： | 2007-05-25 |
Lean Production in Railway Station Traffic Organization Based on PSO-BP Model |
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| Qian Wusheng.Lean Production in Railway Station Traffic Organization Based on PSO-BP Model[J].Journal of Lanzhou Railway University,2007,26(4):29-31,39. |
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| Authors: | Qian Wusheng |
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| Institution: | Kuitun Train Operation Depot, Urumqi Railway Bureau, Kuitun 833200, China |
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| Abstract: | On the basis of the appraisal system of the lean production in railway station traffic organization,the model of the mixed algorithm of PSO(particle swarm optimization) algorithm and BP(back-propagation)network for comprehensive evaluation is presented,which could fully consider factors of railway station traffic organization.Exemplified calculation result shows that PSO-BP model is simple,convenient and universal.The result accords with the reality of producing,indicates well the implementing effect of the lean production in railway traffic organization. |
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| Keywords: | railway station traffic organization lean production BP neural networks particle swarm optimization algorithm |
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