Zhongan Tang
Biographic Data
| ID | 3635385 |
|---|---|
| NAME | Zhongan Tang |
| GIVEN NAMES | Zhongan |
| FAMILY NAME | Tang |
| SIGNATURE | TANG Z |
| AFFILIATIONS | Geospatial Research (United Kingdom) |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios
Rational location planning of express delivery stations (EDS) is crucial for enhancing the quality and efficiency of urban logistics. The spatial heterogeneity of logistics demand across urban areas highlights the importance of adopting a scientific approach to EDS location planning. To tackle the issue of strategy misalignment caused by heterogeneous demand scenarios, this study proposes a continuous location method for EDS based on multi-agent …
Revealing Urban Spatial Interaction Characteristics and Crowd Travel Patterns from Trajectory Data
The accelerated urbanization process has raised higher demands for urban planning and management, and a precise understanding of urban spatial interaction characteristics is fundamental to these efforts. How to uncover the frequent interaction patterns between urban spaces, especially those that exhibit stability over time, and reveal the underlying semantic information, remains a pressing challenge, however. This study proposes a time-sliced mul…
Geographical Scene: The Natural Unit for Geographical Analysis and Its Recognition Based on Data with Spatial and Semantic Features
Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis zones rely heavily on spatial correlations while neglecting semantic relationships between geographical elements. This limitation hinders their ability to captu…
Renovation and Reconstruction of Urban Land Use by a Cost-Heuristic Genetic Algorithm: A Case in Shenzhen
Urban land use multi-objective optimization aims to achieve greater economic, social, and environmental benefits by the rational allocation and planning of urban land resources in space. However, not only land use reconstruction, but renovation, which has been neglected in most studies, is the main optimization direction of urban land use. Meanwhile, urban land use optimization is subject to cost constraints, so as to obtain a more practical opti…
Estimation of travel flux between urban blocks by combining spatio-temporal and purpose correlation
Geographical Scene: The Natural Unit for Geographical Analysis and Its Recognition Based on Data with Spatial and Semantic Features
Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis zones rely heavily on spatial correlations while neglecting semantic relationships between geographical elements. This limitation hinders their ability to captu…
Estimation of travel flux between urban blocks by combining spatio-temporal and purpose correlation
Renovation and Reconstruction of Urban Land Use by a Cost-Heuristic Genetic Algorithm: A Case in Shenzhen
Urban land use multi-objective optimization aims to achieve greater economic, social, and environmental benefits by the rational allocation and planning of urban land resources in space. However, not only land use reconstruction, but renovation, which has been neglected in most studies, is the main optimization direction of urban land use. Meanwhile, urban land use optimization is subject to cost constraints, so as to obtain a more practical opti…
Estimation of travel flux between urban blocks by combining spatio-temporal and purpose correlation
A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios
Rational location planning of express delivery stations (EDS) is crucial for enhancing the quality and efficiency of urban logistics. The spatial heterogeneity of logistics demand across urban areas highlights the importance of adopting a scientific approach to EDS location planning. To tackle the issue of strategy misalignment caused by heterogeneous demand scenarios, this study proposes a continuous location method for EDS based on multi-agent …
Revealing Urban Spatial Interaction Characteristics and Crowd Travel Patterns from Trajectory Data
The accelerated urbanization process has raised higher demands for urban planning and management, and a precise understanding of urban spatial interaction characteristics is fundamental to these efforts. How to uncover the frequent interaction patterns between urban spaces, especially those that exhibit stability over time, and reveal the underlying semantic information, remains a pressing challenge, however. This study proposes a time-sliced mul…
Geographical Scene: The Natural Unit for Geographical Analysis and Its Recognition Based on Data with Spatial and Semantic Features
Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis zones rely heavily on spatial correlations while neglecting semantic relationships between geographical elements. This limitation hinders their ability to captu…
Computer Science (4 works) · Geography (3 works) · Civil engineering (2 works) · Engineering (2 works) · Heuristic (2 works) · Human Mobility and Location-Based Analysis (2 works) · Land use (2 works) · Land Use and Ecosystem Services (2 works) · Mathematics (2 works) · Population (2 works)