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Digital Cities Roadmap
Читать книгу Digital Cities Roadmap - Группа авторов - Страница 1
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Страница 1
Table of Contents
List of Illustrations
List of Tables
Guide
Pages
Страница 7
Страница 8
Страница 9
Страница 10
Preface
Страница 12
1
The Use of Machine Learning for Sustainable and Resilient Buildings
1.1 Introduction of ML Sustainable Resilient Building
1.2 Related Works
1.3 Machine Learning
1.4 What is Resilience?
1.4.1 Sustainability and Resiliency Conditions
1.4.2 Paradigm and Challenges of Sustainability and Resilience
1.4.3 Perspectives of Local Community
1.5 Sustainability and Resilience of Engineered System
1.5.1. Resilience and Sustainable Development Framework for Decision-Making
1.5.2. Exposures and Disturbance Events
1.5.3 Quantification of Resilience
1.5.4 Quantification of Sustainability
1.6 Community and Quantification Metrics, Resilience and Sustainability Objectives
1.6.1 Definition of Quantification Metric
1.6.2 Considering and Community
1.7 Structure Engineering Dilemmas and Resilient Epcot
1.7.1 Dilation of Resilience Essence
1.7.2 Quality of Life
First Dilemma
Second Dilemma
Strategies of Resilience
Third Dilemma
Possible Solution to the Core Resilience Problem
1.8 Development of Risk Informed Criteria for Building Design Hurricane Resilient on Building
1.9 Resilient Infrastructures Against Earthquake and Tsunami Multi-Hazard
1.10 Machine Learning With Smart Building
1.10.1 Smart Building Appliances
1.10.2 Intelligent Tools, Cameras and Electronic Controls in a Connected House (SRB)
1.10.3 Level if Clouds are the IoT Institute Level With SBs
1.10.4 Component of Smart Buildings (SB)
Sensors and Actuators for SBs
Smart Control Devices
Networking and Home Gateway
Machine Learning Framework
1.10.5 Machine Learning Tasks in Smart Building Environment
1.10.6 ML Tools and Services for Smart Building
1.10.7 Big Data Research Applications for SBs in Real-Time
1.10.8 Implementation of the ML Concept in the SB Context
Smart Building Services Taxonomy
1.11 Conclusion and Future Research
References
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