An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning
An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning
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Publisher
Hoboken: Hindawi
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Language
English
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Publisher
Hoboken: Hindawi
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Scope and Contents
Contents
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) and extreme gradient boosting regression (XGBR))...
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Full title
An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning
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TN_cdi_doaj_primary_oai_doaj_org_article_23a5356c1d7046c38c36a0e84b886421
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_23a5356c1d7046c38c36a0e84b886421
Other Identifiers
ISSN
1076-2787
E-ISSN
1099-0526
DOI
10.1155/2022/9928836
