1. Efficiency and Optimization of Buildings Energy Consumption: Volume II.
- Author
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Orosa, José A. and Orosa, José A.
- Subjects
Research & information: general ,Physics ,ventilation ,energy ,COVID-19 ,procedure ,building ,ISO ,energy consumption ,building construction ,Passivhaus ,affordable housing ,neural network ,LSTM ,MLP ,thermal inertia ,building performance ,artificial intelligence ,artificial neural network ,demand-side management ,evolutionary computing ,non-intrusive appliance load monitoring ,parallel computing ,smart grid ,smart house ,cellular concrete ,lightweight materials ,thermal conductivity ,electricity ,dynamic simulation ,housing ,climate change ,weather controlled central system ,energy saving ,thermal improved of buildings ,new energy technologies ,sustainable buildings ,energy efficiency ,heat loss coefficient ,machine learning ,XGBoost ,SVR ,load disaggregation ,multi-scale ,attention mechanism ,residual network ,energy savings ,daylighting ,photovoltaic system ,EnergyPlus ,Homer PRO ,Net Zero Energy Buildings ,solar radiation ,support vector machine ,heuristic algorithm ,renewable energy ,solar energy systems ,n/a - Abstract
Summary: This reprint, as a continuation of a previous Special Issue entitled "Efficiency and Optimization of Buildings Energy Consumption", gives an up-to-date overview of new technologies based on Machine Learning (ML) and Internet of Things (IoT) procedures to improve the mathematical approach of algorithms that allow control systems to be improved with the aim of reducing housing sector energy consumption.