Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting

Machine learning (ML) is capable of accurate Load Forecasting from complete data. However, there are many uncertainties that affect data collection, leading to sparsity. This article proposed a model called Adaptive Ensemble Learning with Gaussian Copula to deal with sparsity, which contains three modules: data complementation, ML construction, and adaptive ensemble. First, it applies Gaussian Copula to eliminate sparsity. Then, we utilise five ML models to make predictions individually. Finally, it employs adaptive ensemble to get final weighted-sum result. Experiments have demonstrated that our model are robust.

Publication Details

Journal
ArXiv.org
Published
2025-08-25
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting

ArXiv.org
Geochemistry and Geologic Mapping
article

Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting

article en

Abstract

Machine learning (ML) is capable of accurate Load Forecasting from complete data. However, there are many uncertainties that affect data collection, leading to sparsity. This article proposed a model called Adaptive Ensemble Learning with Gaussian Copula to deal with sparsity, which contains three modules: data complementation, ML construction, and adaptive ensemble. First, it applies Gaussian Copula to eliminate sparsity. Then, we utilise five ML models to make predictions individually. Finally, it employs adaptive ensemble to get final weighted-sum result. Experiments have demonstrated that our model are robust.

ArXiv.org
Openalex Percentile: Top 64%
Geochemistry and Geologic Mapping
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Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting · ArXiv.org (2025) | TGRS Research Map | TGRS