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Busy Line Analysis with Improved Association Rules Mining Algorithm for Hangzhou Public Free-Bicycle System

机译:杭州市公共自行车系统的改进关联规则挖掘算法的繁忙线路分析

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In China, Hangzhou is the first city to set up the Public Free-Bicycle System. There are many and many technology problems in the decision of intelligent dispatch. In this paper, we investigate the busy line of Hangzhou Public Free-Bicycle System with association rules mining algorithm. Actually, finding association rules is an important data mining problem and can be derived based on mining large frequent candidate sets. In this paper, a new procedure is proposed for efficient generating busy lines candidate set. At first, by passing over the cruel database only once, a rent-return database with entries 1 or 0 are set up. Then, the busy locations and busy lines candidate sets are obtained from the rent-return database. Finally, busy lines are mined from the busy lines candidate sets. Practice examples and comparison with the Apriori Algorithm are made on 4 rent-return databases with small, middle and large sizes from, the West Lake Scenic Zone. It is observed from the experiments that the proposed algorithm is efficient and robust.
机译:在中国,杭州是第一个建立公共免费自行车系统的城市。智能调度决策中存在很多技术问题。本文采用关联规则挖掘算法研究了杭州公交免费系统的繁忙线路。实际上,找到关联规则是重要的数据挖掘问题,并且可以基于挖掘大型频繁候选集而得出。本文提出了一种有效生成忙线候选集的新方法。首先,通过仅使残酷的数据库通过一次,就建立了条目1或0的租金回报数据库。然后,从租金回报数据库中获得繁忙地点和繁忙线路候选者集合。最后,从忙线候选集中挖掘忙线。在来自西湖风景区的4个大小,大小分别为大,小的租金回报数据库中,进行了实践示例并与Apriori算法进行了比较。从实验中可以看出,该算法是有效且鲁棒的。

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