Application of machine learning techniques in railway demand forecasting
Neda Etebari Alamdari, Miguel F. Anjos, Gilles Savard
| Year of publication: |
2021
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|---|---|
| Authors: | Alamdari, Neda Etebari ; Anjos, Miguel F. ; Savard, Gilles |
| Published in: |
International journal of revenue management : IJRM. - Olney, Bucks : Inderscience Enterprises, ISSN 1741-8186, ZDB-ID 2260557-5. - Vol. 12.2021, 1/2, p. 132-151
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| Subject: | revenue management | demand forecasting | feature engineering | machine learning | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Revenue-Management | Revenue management | Nachfrage | Demand | Neuronale Netze | Neural networks | Schienenverkehr | Railway transport |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1504/IJRM.2021.114970 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012521701