A comparative study of demand forecasting models for a multi-channel retail company: a novel hybrid machine learning approach

DOI10.1007/S43069-022-00166-4zbMath1498.90117OpenAlexW4297337538MaRDI QIDQ2084304

Yanyan Li

Publication date: 18 October 2022

Published in: SN Operations Research Forum (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s43069-022-00166-4

zbMATH Keywords

machine learningAdaBooststatistical methodsrandom forestdemand forecastinggradient boostingXGBoost

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Learning and adaptive systems in artificial intelligence (68T05) Management decision making, including multiple objectives (90B50) Transportation, logistics and supply chain management (90B06)

Related Items (1)

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Uses Software

• XGBoost

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