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基于FP-tree算法的船舶滞留原因关联性分析 被引量:2

Correlation analysis of ship detention reasons based on FP-tree algorithm
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摘要 为提高船舶安全检查的效率,提出对港口国监督(Port State Control,PSC)中船舶安全检查要素之间关联性的研究.引入关联规则进行相关性分析,从给定的数据中寻找频繁的项目知识模式,通过置信度和重要性阈值的约束,挖掘出船舶滞留原因间的潜在规律.算例结果表明,通过关联规则对船舶滞留原因的分析,可以直观地发现滞留原因间的关联,利于港口主管机关在实际工作中采取更具针对性的方法进行检查. To improve the efficiency of ship safety inspection,the correlations among ship safety inspec-tion elements of Port State Control are studied. By introducing association rules to analyze the correla-tions,the frequent project knowledge models are found out from the given data. Then through the con-straints of confidence and importance threshold values,the potential laws in ship detention reasons are mined. The result from a case shows that the correlations among ship detention reasons can be directly found out through the association rule analysis,which helps port authorities to take more effective meas-ures in the practical work.
出处 《上海海事大学学报》 北大核心 2015年第2期60-64,83,共6页 Journal of Shanghai Maritime University
基金 浙江海事局项目(201425)
关键词 港口国监督(PSC) 数据挖掘 关联规则 滞留 缺陷 data mining association rule detention deficiency
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