Data-driven Analytics for Sustainable Buildings and Cities

The evolving of data-driven analytics for buildings and cities towards sustainability.-   Data-driven approaches for prediction and classification of building energy consumption.-   Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks.-   Cluster Analysis for Occupant-behaviour based Electricity Load Patterns in Buildings: A Case Study in Shanghai Residences.-   A data-driven model predictive control for lighting system based on historical occupancy in an office building: Methodology development.-  Tailoring future climate data for building energy simulation.-   A solar photovoltaic/thermal (PV/T) concentrator for building application in Sweden using Monte Carlo method.-   Influencing factors for occupants' window-opening behaviour in an office building through logistic regression and Pearson correlation approaches.-   Reinforcement learning methodologies for controlling occupant comfort in buildings.-   A novel Reinforcement learning method for improving occupant comfort via window opening and closing.  2942492291991671341156161