Multi-objective modified satin Bowerbird optimization algorithm used for simulation-based energy consumption optimization of yearly energy demand of lighting and cooling in a test case room
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DOI: 10.1016/j.energy.2024.130508
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- Bui, Dac-Khuong & Nguyen, Tuan Ngoc & Ngo, Tuan Duc & Nguyen-Xuan, H., 2020. "An artificial neural network (ANN) expert system enhanced with the electromagnetism-based firefly algorithm (EFA) for predicting the energy consumption in buildings," Energy, Elsevier, vol. 190(C).
- Chen, Xiao & Cao, Benyi & Pouramini, Somayeh, 2023. "Energy cost and consumption reduction of an office building by Chaotic Satin Bowerbird Optimization Algorithm with model predictive control and artificial neural network: A case study," Energy, Elsevier, vol. 270(C).
- Muhumuza, Ronald & Zacharopoulos, Aggelos & Mondol, Jayanta Deb & Smyth, Mervyn & Pugsley, Adrian, 2018. "Energy consumption levels and technical approaches for supporting development of alternative energy technologies for rural sectors of developing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 90-102.
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Keywords
Energy consumption of the building; Multi-objective modified satin Bowerbird optimization algorithm; Simulation-based optimization; MATLAB; JESS; DesignBuilder;All these keywords.
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