Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia
Rapid population growth and urbanization, coupled with technological advancements, have driven higher electricity demand, predominantly sourced from contributors to climate change. This article introduces a novel artificial intelligence (AI) time-series algorithm, a simple stacked ensemble of simple...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English English |
Published: |
Penerbit UTM
2025
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Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/43575/1/IJBES%20%282025%29.pdf http://umpir.ump.edu.my/id/eprint/43575/7/Enhancing%20electricity%20consumption%20forecasting%20in%20limited%20dataset_A%20simple%20stacked%20ensemble%20approach%20incorporating%20simple%20linear%20and%20support%20vector%20regression%20for%20Malaysia_abs.pdf http://umpir.ump.edu.my/id/eprint/43575/ https://doi.org/10.11113/ijbes.v12.n1.1254 |
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http://umpir.ump.edu.my/id/eprint/43575/1/IJBES%20%282025%29.pdfhttp://umpir.ump.edu.my/id/eprint/43575/7/Enhancing%20electricity%20consumption%20forecasting%20in%20limited%20dataset_A%20simple%20stacked%20ensemble%20approach%20incorporating%20simple%20linear%20and%20support%20vector%20regression%20for%20Malaysia_abs.pdf
http://umpir.ump.edu.my/id/eprint/43575/
https://doi.org/10.11113/ijbes.v12.n1.1254