基于改进熵权聚类SVD的铁路应急救援辅助决策方法

发布时间：2018-05-29 18:53

本文选题：铁路突发事件 + 距离熵　；参考：《铁道学报》2017年08期

【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。
[Abstract]:The method based on clustering analysis and improved distance entropy weight SVD decomposition is applied to railway emergency decision making, which provides a practical and fast method for railway emergency rescue with high dimension and large amount of data. Intelligent auxiliary decision making method. On the basis of combing the characteristic attributes of cases, an improved method of weight acquisition based on distance entropy is proposed. On the premise of reasonably selecting the number of cluster center points, combined with clustering method and weighted SVD decomposition, a railway emergency assistant decision model is constructed. An example is given to illustrate the application of this method to railway emergency decision-making. The case study shows that the clustering analysis and the improved distance entropy weight SVD decomposition method can meet the railway emergency decision demand more accurately and quickly, and provide a new method and a new idea for the railway emergency decision.
【作者单位】：西南交通大学交通运输与物流学院;兰州交通大学自动化与电气工程学院;
【基金】：国家自然科学基金(71173177) 甘肃省青年科技基金(145RJYA242) 兰州交通大学青年科学基金(2015041)
【分类号】：U298.6

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