Using Data Mining to Associating Rules and Predictions on the Traffic Accident Environment

• Main Authors: Min-Liang Chang, 張敏亮
• Other Authors: Hsin-Hung Wu
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/58606835591276353803

碩士 === 臺中健康暨管理學院 === 資訊科學與應用學系碩士班 === 93 === Traffic accidents are one of the critical reasons to cause deaths in Taiwan based upon the Interior Department analysis. One of the most important tasks for our government is to reduce the number of traffic accidents as well as to protect the lives of people in Taiwan. As data mining techniques have been well developed and widely and successfully applied in many areas, this study uses data mining techniques to discover the hidden information in the raw data to provide useful information as a reference by improving the traffic environment. According to the above discussions, this study finds out the reasons that result in traffic accidents by association rules. Moreover, decision trees are applied to provide a clear indication of which fields are most important for prediction or classification as well as to handle both continuous and categorized variables. The relation between the traffic environments and traffic accidents can be used to develop the prediction model that leads more than 60% of accuracy in prediction. Finally, the road hazardous degrees can be defined and the basic expert system for traffic accident analysis can be developed based upon the prediction model.