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Finding Main Causes of Elevator Accidents via Multi-Dimensional Association Rule in Edge Computing Environment 被引量:2

Finding Main Causes of Elevator Accidents via MultiDimensional Association Rule in Edge Computing Environment
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摘要 In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents. In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.
出处 《China Communications》 SCIE CSCD 2017年第11期39-47,共9页 中国通信(英文版)
关键词 elevator group accidents APRIORI multi-dimensional association rules data cube edge computing elevator group accidents apriori multi-dimensional association rules data cube edge computing
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