Predicting the use frequency of ride-sourcing by off-campus university students through random forest and bayesian network techniques

• 主要な著者: Aghaabbasi, M., Shekari, Z. A., Shah, M. Z., Olakunle, O., Armaghani, D. J., Moeinaddini, M.
• フォーマット: 論文
• 出版事項: Elsevier Ltd. 2020
• 主題: NA Architecture
• オンライン･アクセス: http://eprints.utm.my/id/eprint/87092/; http://www.dx.doi.org/10.1016/j.tra.2020.04.013

This study used a survey technique to investigate factors that motivate the adoption and the usage frequency of ride-sourcing among students in a Malaysia public university. Two of the most broadly used machine learning techniques, Random Forest technique and Bayesian network analysis were applied i...