[HTML][HTML] Promising solutions for railway operations to cope with future challenges—Tackling COVID and beyond

Z Wang, J Aoun, C Szymula, N Bešinović - Journal of Rail Transport …, 2023 - Elsevier
The COVID-19 pandemic has imposed a dramatic effect on the mobility habits of both
passengers and freight in the rail sector. Since the relaxation of COVID-19 restrictions …

Real-time prediction of transit origin–destination flows during underground incidents

L Zou, Z Wang, R Guo - Transportation Research Part C: Emerging …, 2024 - Elsevier
Efficient transportation planning and management are critical for ensuring the smooth
operation of rail transit systems, particularly in urban areas with high passenger demand …

[HTML][HTML] Fare revenue forecast in public transport: a comparative case study

J Krembsler, S Spiegelberg, R Hasenfelder… - Research in …, 2024 - Elsevier
This paper presents results from a case study of fare revenue prediction in public
transportation in Berlin using machine learning and time series analysis. Our work aims to …

A Low-Rank Bayesian Temporal Matrix Factorization for the Transfer Time Prediction Between Metro and Bus Systems

P Wu, M Pei, T Wang, Y Liu, Z Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Accurate transfer time prediction and future transfer time information are important for both
public transport operators and passengers. However, existing studies cannot effectively …

[PDF][PDF] Journal of Rail Transport Planning & Management

Z Wang, J Aoun, C Szymula… - Journal of Rail Transport …, 2022 - researchgate.net
ABSTRACT Automatic Train Operation (ATO) is well-known in urban railways and gets
increasing interest from mainline railways at present to improve capacity and punctuality. A …

Beyond the Lab: Exploring the Socio-Technical Implications of Machine Learning in Biopharmaceutical Manufacturing

E Flores-García, SH Nam, Y Jeong… - … on Advances in …, 2023 - Springer
In the data-rich but knowledge-poor domain of production management systems, the
utilization of machine learning (ML) for lead-time prediction has gained increasing attention …

Prediction of railroad user count using number of route searches via bivariate state–space modeling

M Kuwano, M Hosoe, T Moriyama - The Journal of Supercomputing, 2024 - Springer
Conventional demand-prediction methods predominantly rely on past user behaviors to
predict regular future transportation demands using acquired user preference data …

Real-Time Prediction of Transit OD Under Underground Incidents

L Zou, Z Wang, R Guo - Available at SSRN 4529913 - papers.ssrn.com
Efficient transportation planning and management are critical for ensuring the smooth
operation of rail transit systems, especially in urban areas with high passenger demands …

[PDF][PDF] バス停間の乗客数の相関と日時や天候の影響を考慮したLSTM に基づく乗客数予測手法

山村竜也, ヤマムラタツヤ - 2023 - naist.repo.nii.ac.jp
修士論文 バス停間の乗客数の相関と日時や天候の影響を考慮した LSTMに基づく乗客数予測手法
Page 1 修士論文 バス停間の乗客数の相関と日時や天候の影響を考慮した LSTMに基づく乗客数 …