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Efficiency and Optimization of Buildings Energy Consumption: Volume II
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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.
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Keywords
- affordable housing
- artificial intelligence
- artificial neural network
- attention mechanism
- Building
- building construction
- Building performance
- cellular concrete
- Climate Change
- COVID-19
- daylighting
- demand-side management
- dynamic simulation
- Electricity
- energy
- Energy consumption
- Energy Efficiency
- energy saving
- energy savings
- EnergyPlus
- evolutionary computing
- heat loss coefficient
- heuristic algorithm
- HOMER Pro
- Housing
- ISO
- lightweight materials
- load disaggregation
- LSTM
- Machine learning
- Mathematics & science
- MLP
- multi-scale
- n/a
- Net Zero Energy Buildings
- Neural Network
- new energy technologies
- non-intrusive appliance load monitoring
- parallel computing
- passivhaus
- photovoltaic system
- Physics
- procedure
- Reference, information & interdisciplinary subjects
- renewable energy
- Research & information: general
- residual network
- Smart grid
- smart house
- solar energy systems
- Solar radiation
- support vector machine
- Sustainable buildings
- SVR
- thermal conductivity
- thermal improved of buildings
- thermal inertia
- Ventilation
- weather controlled central system
- XGBoost
Links
DOI: 10.3390/books978-3-0365-6507-1Editions