2024
DOI: 10.1108/gs-01-2024-0011
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Improving electricity demand forecasting accuracy: a novel grey-genetic programming approach using GMC(1,N) and residual sign estimation

Flavian Emmanuel Sapnken,
Benjamin Salomon Diboma,
Ali Khalili Tazehkandgheshlagh
et al.

Abstract: PurposeThis paper addresses the challenges associated with forecasting electricity consumption using limited data without making prior assumptions on normality. The study aims to enhance the predictive performance of grey models by proposing a novel grey multivariate convolution model incorporating residual modification and residual genetic programming sign estimation.Design/methodology/approachThe research begins by constructing a novel grey multivariate convolution model and demonstrates the utilization of g… Show more

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Cited by 3 publications
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