High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case-Reference-Cited by-同舟云学术

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High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case

Published:2024-12 Issue: Volume:258 Page:125196
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Huang Wencheng^ORCID,Yin Yanhui,Li Haoran,Xie Anhao,Fan Yuzhou

Funder

Natural Science Foundation of Sichuan Province

Central University Basic Research Fund of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference79 articles.

1. Unidirectional and bidirectional lstm models for short-term traffic prediction;Abduljabbar;Journal of Advanced Transportation,2021

2. Why did you predict that? Towards explainable artificial neural networks for travel demand analysis;Alwosheel;Transportation Research Part C: Emerging Technologies,2021

3. Peeking inside the black-box: Explainable machine learning applied to household transportation energy consumption;Amiri;Computers, Environment and Urban Systems,2021

4. Railway freight volume forecasting based on unbiased grey Verhulst model;An;Journal of Railway Science and Engineering,2016

5. Express delivery with high-speed railway: Definitely feasible or just a publicity stunt;Bi;Transportation Research Part A,2019

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