Neural network architecture for the estimation of drivers' route choice

被引:0
|
作者
Kyung Whan Kim
Dae Hyon Kim
Hyun Yeal Seo
机构
[1] College of Engineering,Urban Engineering Major, Division of Construction Engineering
[2] Gyeongsang National University,Environment & Regional Development Institute
[3] Yosu National University,Transportation Engineering Major, Division of Transportation & Logistics System Engineering
[4] Gyeongsang National,Department of Urvan Engineering, Graduate School
关键词
artificial neural network; customized neural network; logit model; route choice;
D O I
10.1007/BF02829155
中图分类号
学科分类号
摘要
The artificial neural network has recently been applied in many areas including transport engineering and planning. However, since the general neural network considers all the listed variables in a batch, the network seemed to be unsophisticated. A more sophisticated neural network model therefore had to be developed. In this study, a sophisticated neural network model was developed for drivers' route choice model. Its performance was then compared with the performance of the Logit model. For the development of the neural network model, two different neural network models-the general neural network model and the customized neural network model whose architecture is similar to the Logit models-were considered. The results showed that the customized neural network could perform better than other models in terms of prediction accuracy and goodness-of-fit.
引用
收藏
页码:329 / 336
页数:7
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