An ANFIS-Fuzzy Tree-GA Model for a Hospital’s Electricity Purchasing Decision-Making Process Integrated with Virtual Cost Concept
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- George Kyriakarakos & Anastasios Dounis, 2020. "Intelligent Management of Distributed Energy Resources for Increased Resilience and Environmental Sustainability of Hospitals," Sustainability, MDPI, vol. 12(18), pages 1-4, September.
- Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2017. "User satisfaction-induced demand side load management in residential buildings with user budget constraint," Applied Energy, Elsevier, vol. 187(C), pages 352-366.
- Khaled Bawaneh & Farnaz Ghazi Nezami & Md. Rasheduzzaman & Brad Deken, 2019. "Energy Consumption Analysis and Characterization of Healthcare Facilities in the United States," Energies, MDPI, vol. 12(19), pages 1-20, October.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
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Keywords
electricity price prediction; adaptive neuro-fuzzy system; fuzzy trees; genetic algorithms; healthcare facilities; sustainable hospitals;All these keywords.
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