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Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector
Prediction and Correlation Analysis of Heating Energy Consumption in Four Residential Apartments with Sensitivity Analysis Using Long Short-Term Memory (Lstm) and Generalized Regression Neural Network (Grnn)
Using artificial intelligence models and degree-days method to estimate the heat consumption evolution of a building stock until 2050: A case study in a temperate climate of the Northern part of Europe
Interpretable probabilistic forecasting of building multi-energy loads using residual learning and global attention-enabled transformer: A case study for residential buildings in South Korea
A calibrated white-box digital twin for predictive blind control: A passive strategy to balance solar-driven thermal loads mitigation and daylight availability
A methodological review on management of building cluster meso energy hubs in accordance with the agile framework: Exploring flexibility upward the building-cluster-city hierarchy
Predictive and correlational analysis of heating energy consumption in four residential apartments with sensitivity analysis using long Short-Term memory and Generalized regression neural network models
Parameter identification approach to represent building thermal dynamics reducing tuning time of control system gains: A case study in a tropical climate
Development of an AI Model Utilizing Buildings’ Thermal Mass to Optimize Heating Energy and Indoor Temperature in a Historical Building Located in a Cold Climate
Une méthodologie d'aide à la décision basée sur l'ACV dynamique pour la gestion du budget carbone des bâtiments
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