An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning

An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning

This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. Bagging (random forest regression (RFR)), boosting (gradient boosting regression (GBR...

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Bibliographic Details
Main Authors:	S. M. Taslim Uddin Raju, Amlan Sarker, Apurba Das, Md. Milon Islam, Mabrook S. Al-Rakhami, Atif M. Al-Amri, Tasniah Mohiuddin, Fahad R. Albogamy
Format:	Article
Language:	English
Published:	Wiley 2022-01-01
Series:	Complexity
Online Access:	http://dx.doi.org/10.1155/2022/9928836
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