Improving electricity demand forecasting accuracy: a novel grey-genetic programming approach using GMC(1,N) and residual sign estimation

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@Article{DBLP:journals/gsta/SapnkenDTHNWT24,

• author = "Flavian Emmanuel Sapnken and Benjamin Salomon Diboma and Ali Khalili Tazehkandgheshlagh and Mohammed Hamaidi and Prosper Gopdjim Noumo and Yong Wang and Jean Gaston Tamba",
• title = "Improving electricity demand forecasting accuracy: a novel grey-genetic programming approach using GMC(1,N) and residual sign estimation",
• journal = "Grey Syst. Theory Appl.",
• volume = "14",
• number = "4",
• pages = "708--732",
• year = "2024",
• keywords = "genetic algorithms, genetic programming",
• URL = "https://doi.org/10.1108/GS-01-2024-0011",
• DOI = "doi:10.1108/GS-01-2024-0011",
• timestamp = "Wed, 30 Oct 2024 00:00:00 +0100",
• biburl = "https://dblp.org/rec/journals/gsta/SapnkenDTHNWT24.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",

}

Genetic Programming entries for Flavian Emmanuel Sapnken Benjamin Salomon Diboma Ali Khalili Tazehkandgheshlagh Mohammed Hamaidi Prosper Gopdjim Noumo Yong Wang Jean Gaston Tamba

Citations