The Day-Ahead Forecasting of the Passenger Occupancy in Public Transportation by Using Machine Learning

Author:

Altıntaş AtillaORCID,Davidson LarsORCID,Kostaras Giannis,Isaac Maycel

Publisher

Springer International Publishing

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine Learning for public transportation demand prediction: A Systematic Literature Review;Engineering Applications of Artificial Intelligence;2024-11

2. Predicting Passenger Occupancy of Commercial Buses Using Regression Approach of Machine Learning;2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA);2023-11-14

3. Improving the Prediction of Passenger Numbers in Public Transit Networks by Combining Short-Term Forecasts With Real-Time Occupancy Data;IEEE Open Journal of Intelligent Transportation Systems;2023

4. Forecasting of Day-Ahead Wind Speed/electric Power by Using a Hybrid Machine Learning Algorithm;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2023

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