Apriori算法实现基于关联规则的交通路段流量挖掘

时空数据挖掘技术是城市交通出行决策系统的一个重要的数据处理环节,其分析结果也是路网疏导和出行策略的重要决定因素.对著名的Apriori算法加以完善和应用,已成为城市交通出行决策系统中时空数据挖掘的研究热点.以某城市的路段流量为例,利用Apriori算法对路段流量间的时空关联规则进行挖掘.测试结果与实际数据对比,预测结果精度较高.

Mining of Road Traffic Flows Based on Association Rules by Using Apriori Algorithm

Temporal-spatial data mining technology is an important aspect of data processing in the urban traffic decision system,and its analysis result is a key factor to make decision of road network diverting and travel strategy. Improvement and application of the famous Apriori algorithm has become a research hotspot in temporal-spatial data mining for the urban traffic decision system. Taking some roads＇ traffic flows of a real city as an example, mining of the traffic flow data in temporal-spatial association rules based on the Apriori algorithm was conducted. Comparing the prospected results with the real data,the former has a higher precision.