Q.Pan
phd
Title
Summary
Samenvatting
Acknowledgement
Abbreviations
1. Introduction
1.1. Background
1.2. Case Studies
1.3. Research Objectives
1.4. Innovation and Practical Value
1.5. Thesis Outline
2. Literature Review
2.1. Simulation Modelling
2.2. Multi-objective Optimisation Algorithms
2.3. Surrogate Modelling
2.4. Decision Support System
3. Methodology
3.1. General
3.2. Simulation Modelling
3.3. Simulation Model Based Optimisation
3.4. Surrogate Model Based Optimisation
3.5. Decision Support Framework
4. Milano Water Supply Network Simulation Model
4.1. Data Collection and Analysis
4.2. Simulation Model Setup
4.2. Simulation Results
5. Taihu Lake Water Quality Simulation Model
5.1. Data Collection and Analysis
5.2. Simulation Model Setup
5.2. Simulation Results
6. Milano Pump Scheduling Problem Optimisation
6.1. Problem Description
6.2. Optimisation Results
7. Taihu Lake Waste Load Control Problem Optimisation
7.1. Problem Description
7.2. Optimisation Results
8. Surrogate Model Based Taihu Lake Waste Load Control Problem Optimisation
8.1. Problem Description
8.2. Surrogate Model Setup
8.3. Surrogate Model Results
9. Decision Support Framework Development
9.1. DSF Generic Design
9.2. DSF Components
9.3. DSF Implementation
10. Conclusions and Recommendations
10.1. Conclusions
10.2. Recommendations
References
Appendix
Author
Powered by
GitBook
8.2. Surrogate Model Setup
8.2. Surrogate Model Setup
8.2.1. Training Dataset
8.2.2. Low Fidelity Model
8.2.3. Model Accuracy
8.2.4. Surrogate Model Based Optimisation Approaches
results matching "
"
No results matching "
"