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...

Full description

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

Internet

http://www.sciencedirect.com/science/article/pii/S2772671123002875

Similar Items