Data-driven Analytics for Sustainable Buildings and Cities : From Theory to Application /
This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heatin...
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| Format: | eBook |
| Language: | English |
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Singapore :
Springer Singapore : Imprint: Springer,
2021.
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| Edition: | 1st ed. 2021. |
| Series: | Sustainable Development Goals Series,
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- 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.