Intro
Preface
Organization
Contents
Urban Computing and Social Governance
Resilience-Based Epidemic Strategy Evaluation Method Under Post-Covid-19
1 Introduction
2 Theoretical Basis
2.1 Urban Subsystems Applied to Resilience
2.2 Resilience Concept Applied to Urban System
2.3 Strategy Evaluation Method Applied to Urban Resilience
3 Strategy Evaluation Framework
4 Case Analysis and Discussion
4.1 Identifying Evaluable Strategies
4.2 Identifying Evaluable Strategies
4.3 Resilience Capacity Index System of Urban Social System Under Epidemic

4.4 Accumulation
4.5 Discussion
5 Conclusion
References
The Effects of Intervention Strategies for COVID-19 Transmission Control on Campus Activity
1 Introduction
2 Methodology
2.1 Model of Infection Risk
2.2 Case Design
3 Results
3.1 The Transmission of COVID-19 Caused by the Alumni Group for the Baseline Case
3.2 The Effect of Ventilation, Social Distancing and Wearing Mask on COVID-19 Transmission
3.3 The Impact of Combined Intervention Measures on the COVID-19 Transmission
4 Discussion
4.1 The Transmission Risk Brought by Staff During the Anniversary

4.2 The Comparison of Cases with Different Initial Infector Proportions
4.3 The Limitations of This Study
5 Conclusions
References
Social Resilience Assessment for Urban System: A Case Study of COVID-19 Epidemic
1 Introduction
2 Gap Analysis-Based Assessment Method
3 Case Analysis of COVID-19 Epidemic
3.1 Materials and Methods
3.2 Data Analysis Results
3.3 Resilience Analysis
4 Discussion
5 Conclusion
References
Prediction of Female Fertility Structure and Population Change in China by Modified SIR Model
1 Introduction

2 SIR Fertility Structure and Population Prediction Model
2.1 Model Front
2.2 Basic Prediction Model
2.3 Parameters of the Model
3 Data Source and Parameter Setting
3.1 Data Sources
3.2 Parameter Setting
4 Analysis of Empirical Results
4.1 SIR Population Model Prediction Analysis
4.2 Model Prediction Error Validation Analysis
4.3 Model Prediction of Future Population Scenarios
5 Conclusion
References
Generative Adversarial Network for Imputation of Road Network Traffic State Data
1 Introduction
2 Methodology
2.1 Data Preprocessing

2.2 The Feature Abstraction of Road Network Based on GAE
2.3 The Design of Generative Adversarial Network for Spatio-Temporal Feature Based on LSTM
2.4 The Imputation of Road Network Data Based on GAE-GAN
3 Experiment
3.1 Experimental Design
3.2 Parameter Setting and Model Index
4 Results and Discussion
4.1 Effectiveness of GAE
4.2 Effectiveness of Internal Structure of Generator (LSTM)
4.3 Comparison with Other Models
5 Conclusions
References
Artificial Intelligence and Cognitive Science