Prediction of the impact of typhoons on transportation networks with support vector regression

Ta Yin Hu, Wei Ming Ho

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

The ability to predict the impact of typhoons on transportation infrastructure is important as it can help to avoid serious delays and dangers when roads are closed due to such events. This research uses support vector regression (SVR) to predict the impact of typhoons on transportation infrastructure. It first integrates and examines the infrastructure and precipitation data from different authorities. An SVR model is constructed to solve a nonlinear prediction problem for small size data. The SVR model is calibrated and validated by a heuristic process. The calibrated and validated results are then applied to predict closed roads in a real network through a simulation assignment model. Several traffic management strategies are developed to reduce the negative impacts of typhoons. The results show that the mean absolute percentage error (MAPE) of SVR prediction is 9.7%. The impact of typhoons on transportation networks can thus be predicted and simulated based on the calibrated SVR model, and appropriate strategies can then be developed in order to reduce both delays and risks.

原文English
文章編號04014089
期刊Journal of Transportation Engineering
141
發行號4
DOIs
出版狀態Published - 2015 四月 1

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Transportation

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