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An assertive reasoning method for emergency response management based on knowledge elements C4.5 decision tree

机译:基于知识元素C4.5决策树的突发事件管理的主观推理方法

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The correct selection of knowledge elements is the key to emergency management. Using emergency knowledge elements, this study constructs an assertive reasoning selection methodology by improving acquisition on the balance coefficient in the C4.5 algorithm. Through hierarchical representation, a two level model selection method, based on a top model construction process as well as an underlying model selection process, is proposed. Specifically, the top model construction process is based on assertive reasoning and an underlying model selection process is based on the C4.5 decision tree. This method reduces the requirements for emergency domain knowledge, and improves the accuracy and timeliness. Lastly, the methodology is applied to the 2015 Tianjin explosions as a case study. (C) 2018 Elsevier Ltd. All rights reserved.
机译:正确选择知识要素是应急管理的关键。本研究使用紧急知识元素,通过改善C4.5算法中平衡系数的获取,构建了一个自信的推理选择方法。通过分层表示,提出了一种基于顶层模型构建过程和底层模型选择过程的二级模型选择方法。具体来说,顶级模型构建过程基于主观推理,而基础模型选择过程则基于C4.5决策树。该方法减少了对紧急领域知识的需求,并提高了准确性和及时性。最后,该方法作为案例研究应用于2015年天津爆炸。 (C)2018 Elsevier Ltd.保留所有权利。

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