A two‐stage forecasting approach for short‐term intermodal freight prediction
Abstract
The forecasting of the freight transportation, especially the short‐term case, is an important topic in the daily supply chain management. Intermodal freight transportation is subject to multiple complex calendar effects arising in the port environment. The use of prediction methods provides information that may be helpful as a decision‐making tool in the management and planning of operations processes in ports. This work addresses the forecasting problem on a daily basis by a novel two‐stage scheme combination to offer reliable predictions of fresh freight weight on Ro‐Ro (roll‐on/roll‐off) transport for 7 and 14 days ahead. The study compares daily forecasting with a weekly forecasting approach. The applies database preprocessing and Bayesian regularization neural networks (BRNN) in Stage I. In Stage II, an ensemble framework of the best BRNN models is used to enhance the Stage I forecasting. The results show that the models assessed are a promising tool to predict freight time series for Ro‐Ro transport.
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ML can contribute by improving predictions of estimated time of arrival or weight/volume of expected freight.
“ML can contribute by improving predictions of the estimated time of arrival (for example, of freight trains [56]) or the weight or volume of expected freight (for example, for roll-on/roll-off transport-often abbreviated as Ro-Ro [560]).”
From Tackling climate change with machine learning (2023) · cites this paper as [560]
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Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
- Authors
- Moscoso‐López, J. A., Turias, I., Jiménez‐Come, M. J., Ruiz‐Aguilar, J. J., & Cerbán, M. D. M.
- Affiliations
- Universidad de Cádiz (ES)
- Intelligent Modelling of Systems Research Group Polytechnic School of Engineering (Algeciras) University of Cádiz Algeciras, Cádiz Spain
- Corresponding author
- Moscoso‐López, José Antonio
- Turias, Ignacio
- Cerbán, María del Mar
- Venue
- International Transactions in Operational Research
- Publisher
- Wiley
- Published
- 2016-09-02
- Volume
- 26
- Issue
- 2
- Pages
- 642-666
- ISSN
- 0969-6016 (ISSN-L)
- 1475-3995
- OpenAlex
- W2514487482
- Cited by
- 25
- References
- 61
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 5 · 2021: 3 · 2020: 5 · 2019: 2 · 2018: 1 · 2017: 1
- FWCI
- 1.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Transactions in Operational Research (publishedVersion)
- Funders
- Universidade do Porto
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Maritime Ports and Logistics
- Physical Sciences › Engineering › Building and Construction › Traffic Prediction and Management Techniques
- Keywords
- intermodal freight transport, Bayesian regularization neural network, ensemble forecasting, two-stage forecasting, calendar anomalies
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