Strategies for predictive power: Machine learning models in city-scale load forecasting

Strategies for predictive power: Machine learning models in city-scale load forecasting

This study focuses on enhancing machine learning (ML) algorithms' performance in predicting daily loads for Kirkuk, Iraq—an essential element in energy planning, resource allocation, and policymaking. We explore single and ensemble learning algorithms, including AdaBoost, Bagging, Support Vecto...

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Bibliographic Details
Main Authors:	Orhan Nooruldeen, Mohammed Rashad Baker, A.M. Aleesa, Ahmed Ghareeb, Ehab Hashim Shaker
Format:	Article
Language:	English
Published:	Elsevier 2023-12-01
Series:	e-Prime: Advances in Electrical Engineering, Electronics and Energy
Subjects:	Load forecasting Electricity planning Machine learning Ensemble learning Feature reduction Kirkuk city
Online Access:	http://www.sciencedirect.com/science/article/pii/S2772671123002875

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