Reinforcement learning framework for freight demand forecasting to support operational planning decisions
Lama Al Hajj Hassan, Hani S. Mahmassani, Ying Chen
| Year of publication: |
2020
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|---|---|
| Authors: | Hassan, Lama Al Hajj ; Mahmassani, Hani S. ; Chen, Ying |
| Published in: |
Transportation research / E : an international journal. - Amsterdam : Elsevier, ISSN 1366-5545, ZDB-ID 1380969-6. - Vol. 137.2020, p. 1-20
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| Subject: | Freight demand forecasting | Reinforcement learning | Rolling horizon | Time series | Prognoseverfahren | Forecasting model | Nachfrage | Demand | Güterverkehr | Freight transport | Lernprozess | Learning process | Theorie | Theory | Lernen | Learning |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.tre.2020.101926 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012236690