通过优化的随机森林分类器识别出行方式选择的显著特征及其预测:对主动通勤行为的评估

作者: 时间:2022-06-17 点击数:

Nur Fahriza Mohd Ali, Ahmad Farhan Mohd Sadullah, Anwar PP Abdul Majeed, Mohd Azraai Mohd Razman, Rabiu Muazu Musa



    Physical activity is the foundation to staying healthy, but sedentary activities have become not uncommon that ought to be mitigated immediately. The study aims to highlight the role of a transport system that encourages physical activity among users by applying an active door-to-door transport system. Users’ mode choice is studied to understand their preferences for active commuting. The use of machine learning has since been ubiquitous in a myriad of fields, including transportation studies and hence is also investigated towards its efficacy in predicting travel mode choice.

DOI:https://doi.org/10.1016/j.jth.2022.101362

Date:2022-6-1


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