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基于改进熵权聚类SVD的铁路应急救援辅助决策方法
作者: 静1 2  斌1 何凯妮1  鹏1 
单位:1. 西南交通大学 交通运输与物流学院,四川 成都 610031;2. 兰州交通大学 自动化与电气工程学院,甘肃 兰州 730070
关键词:铁路突发事件 距离熵 奇异值分解 聚类 应急决策 
分类号:
出版年·卷·期(页码):2017·39·第8期(18-26)
摘要:

将基于聚类分析与改进距离熵权SVD分解的方法应用到铁路突发事件应急决策中,为具有高维、大量数据特点的铁路突发事件应急救援提供一种实用、快速、智能的辅助决策方法。在对案例特征属性梳理的基础上,提出改进距离熵的权重获取方法。在给出合理选取聚类中心点个数方法的前提下,结合聚类方法和加权SVD分解构建铁路突发事件应急辅助决策模型。通过具体算例说明该方法用于铁路突发事件辅助决策的过程。案例分析表明,基于聚类分析与改进距离熵权SVD分解的方法能够较准确且快速地满足铁路应急决策需求,为铁路突发事件应急辅助决策提供了新方法、新思路。

The application of the method based on clustering analysis and improved distance entropy method SVD decomposition to the railway emergency decision provides a practical, quick and intelligent assistant decision-making method for railway emergency rescue with high dimension and large data characteristics. The method to extract the improved distance entropy weight was put forward by analyzing the characteristics of the case. On the condition that the number of cluster center points was selected reasonably, the railway emergency assistant decision-making model was built based on the weighted SVD and the clustering method. The process of using this method in railway emergency decision making was illustrated by a specific example. The case analysis shows that the method based on clustering analysis and improved distance entropy weighted SVD can meet the needs of railway emergency decision, and provide a new method and idea for the railway emergency decision making.

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