Optimizing electric load forecasting with support vector regression/LSTM optimized by flexible Gorilla troops algorithm and neural networks a case study

Optimizing electric load forecasting with support vector regression/LSTM optimized by flexible Gorilla troops algorithm and neural networks a case study

Abstract This research work focuses on addressing the challenges of electric load forecasting through the combination of Support Vector Regression and Long Short-Term Memory (SVR/LSTM) methodology. The model has been modified by a flexible version of the Gorilla Troops optimization algorithm. The ob...

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Bibliografiske detaljer
Main Authors: Zhirong Zhang, Qiqi Zhang, Haitao Liang, Bizhan Gorbani
Format: Article
Sprog:English
Udgivet: Nature Portfolio 2024-09-01
Serier:Scientific Reports
Fag:
Electric load forecasting
Support Vector Regression
Long short-term memory
Flexible gorilla troops optimization algorithm
Online adgang:https://doi.org/10.1038/s41598-024-73893-9

Internet

https://doi.org/10.1038/s41598-024-73893-9

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