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Application of Case Retrieval Algorithm Based on Variable Weighted Grey Relation in Urban Rail Transit Network Operation Pattern Database

机译:基于可变加权灰色关系的案例检索算法在城市轨道交通网络操作模式数据库中的应用

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Under networked conditions, the growing number of subway lines means exponential increase in energy consumption. In an emergency, if the train still executes the previous operation chart, it will consume more energy. Therefore, the main research problem of this article is to quickly find the operation diagram suitable for the train's emergency situation in the current networked line through the improvement of the case database design, so as to achieve the optimal total energy consumption of the subway network and achieve the purpose of energy saving. Based on the relevant theories of case-based reasoning, this paper introduces a comprehensive weight adjustment method based on rough set and conditional information entropy method, and a case retrieval method based on two-stage variable weight gray correlation degree in the urban rail transit network operation pattern database applications.
机译:在网络条件下,越来越多的地铁线意味着能量消耗的指数增加。在紧急情况下,如果火车仍然执行以前的操作图表,它将消耗更多的能量。因此,本文的主要研究问题是通过改进案例数据库设计,快速找到适合火车的紧急情况的操作图,从而实现地铁网络的最佳总能耗。达到节能的目的。基于基于案例推理的相关理论,本文介绍了基于粗糙集和条件信息熵方法的全面重量调整方法,以及基于城市轨道交通网络两级可变权重灰色相关程度的案例检索方法操作模式数据库应用程序。

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