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Knowledge Discovery Database (KDD)-Data Mining Application in Transportation

机译:知识发现数据库(KDD)-数据挖掘在运输中的应用

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摘要

In this paper, an understanding and a review of data mining (DM) development and its applications in logistics and specifically transportation are highlighted. Even though data mining has been successful in becoming a major component of various business processes and applications, the benefits and real-world expectations are very important to consider. It is also surprising to note that very little is known to date about the usefulness of applying data mining in transport related research. From the literature, the frameworks for carrying out knowledge discovery and data mining have been revised over the years to meet the business expectations. In this paper, we apply CRISP-DM for formulating effective tire maintenance strategy within the context of a Malaysian\u27s logistics company. The results of applying CRISP-DM for tire maintenance decisions are presented and discussed.
机译:在本文中,重点介绍了对数据挖掘(DM)的开发及其在物流特别是运输中的应用的理解和回顾。尽管数据挖掘已成功地成为各种业务流程和应用程序的主要组成部分,但要考虑的好处和实际期望也非常重要。令人惊讶的是,迄今为止,人们对将数据挖掘应用于运输相关研究的有用性知之甚少。根据文献,多年来,为了满足业务期望,对用于进行知识发现和数据挖掘的框架进行了修订。在本文中,我们将CRISP-DM用于在马来西亚物流公司的背景下制定有效的轮胎维护策略。介绍并讨论了将CRISP-DM用于轮胎维护决策的结果。

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