基于数据挖掘的增城居民出行特征分析

针对目前居民出行调查的特征分析，主要以统计分析为主，为了进一步深入挖掘调查数据内部隐含的信息，通过数据挖掘技术对居民出行调查数据进行研究。在神经网络算法确定出居民出行方式的重要度后，对数据挖掘的数据进行精简，随后应用决策树算法，分析选择不同出行方式的特征。并以增城居民出行调查为例，分析增城居民出行的特征，给出相关规划建议，验证了该数据挖掘流程的有效性，可以为相关部门制定决策提供理论支持。

Analysis of Resident Trip Characteristics Based on Data Mining

For characteristic analysis of resident trip survey, statistical analysis is the mainstream way at present. In order to further mining the underlying information of survey data, data mining techniques are used in this study. After the importance of resident trip modes were determined with the neural network algorithm, the data of data mining were reduced, then the decision tree algorithm was used to analyze different trip modes. Take the resident trip survey in Zengcheng, for example. Based on characteristic analysis of resident trip modes, some planning advices were offered, so this data mining process which was validated could offer theoretical support for decision-making of relevant departments.