Applying Data Mining Technology for the factor of running of car about time –Illustrated by the case of toll station in Houli

• Main Authors: Yan-Chang Chen, 陳炎長
• Other Authors: Ta-Cheng Chen
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/pk4j5h

碩士 === 國立虎尾科技大學 === 資訊管理研究所 === 99 === Conventional fare collection system has been successfully applied to freeway toll station for a long period. Because of the rapid development of the econmy in Taiwan, the amount of cars grows by 200 thousands per year. It deeply affects the traffic quality. Decrease the vehicle frequency by fare collection has been broadly adoped to improve the flow by other countries. However, in holidays, traffic congestion still occurs in the toll station areas. In order to improve the traffic jams caused by fee collection, this study tries to realize the relationship between time factor and vehicle flow. Discuss the the reasons of the traffic congestion hapeend in fee collection stations by behaviorual theory. During the process, we set the value of attribute “the importance of deleting and modifying” to 75%, as well as the value of “Minimum records per child branch” to 2. The historial data is derived from bi-directional vehicle flow of Hou-Li toll station. The accuracy rate of the test result is higher than 94%, which can support our hypothesis and predictions. Finally, we also perform the decision-tree algorithm to examine the corresponding flows in weekends, weekdays and consecutive holidays. The results demonstrate that traffic flow has definitely relationship with the type of holidays.