A comparative analysis and ensemble approach of VAR, XGBoost & LSTM for Forecasting Solar Energy Generation

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Keywords	Forecasting, Renewable Energy, Energy Transition, Machine Learning, Deep Learning
Thesis Advisor	Aghamohammadzadeh, Ehsan, Tsoukalas, Angelos
Persistent URL	hdl.handle.net/2105/72043
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Meneres Calheiros Döbele, Mateus. (2024, July 9). A comparative analysis and ensemble approach of VAR, XGBoost & LSTM for Forecasting Solar Energy Generation. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/72043

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