Zhuhua Liao
Biographic Data
| ID | 9923082 |
|---|---|
| NAME | Zhuhua Liao |
| GIVEN NAMES | Zhuhua |
| FAMILY NAME | Liao |
| SIGNATURE | LIAO Z |
| AFFILIATIONS | Hunan University of Science and Technology |
| ORCID | 0000-0001-9720-7910 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Multi-Type Features Embedded Deep Learning Framework for Residential Building Prediction
Building type prediction is a critical task for urban planning and population estimation. The growing availability of multi-source data presents rich semantic information for building type prediction. However, existing residential building prediction methods have problems with feature extraction and fusion from multi-type data and multi-level interactions between features. To overcome these limitations, we propose a deep learning approach that ta…
Analysis and Forecast of Traffic Flow between Urban Functional Areas Based on Ride-Hailing Trajectories
Urban planning and function layout have important implications for the journeys of a large percentage of commuters, which often make up the majority of daily traffic in many cities. Therefore, the analysis and forecast of traffic flow among urban functional areas are of great significance for detecting urban traffic flow directions and traffic congestion causes, as well as helping commuters plan routes in advance. Existing methods based on ride-h…
Road Intersection Recognition via Combining Classification Model and Clustering Algorithm Based on GPS Data
Road intersections are essential to road networks. How to precisely recognize road intersections based on GPS data is still challenging in intelligent transportation systems. Road intersection recognition involves detecting intersections and recognizing its scope. There are few works on intersections’ scope recognition. The existing methods always focus on road intersection detection. It includes two parts: one is selecting turning points from GP…
Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we…
No prominent works on this page.
Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we…
Road Intersection Recognition via Combining Classification Model and Clustering Algorithm Based on GPS Data
Road intersections are essential to road networks. How to precisely recognize road intersections based on GPS data is still challenging in intelligent transportation systems. Road intersection recognition involves detecting intersections and recognizing its scope. There are few works on intersections’ scope recognition. The existing methods always focus on road intersection detection. It includes two parts: one is selecting turning points from GP…
Multi-Type Features Embedded Deep Learning Framework for Residential Building Prediction
Building type prediction is a critical task for urban planning and population estimation. The growing availability of multi-source data presents rich semantic information for building type prediction. However, existing residential building prediction methods have problems with feature extraction and fusion from multi-type data and multi-level interactions between features. To overcome these limitations, we propose a deep learning approach that ta…
Analysis and Forecast of Traffic Flow between Urban Functional Areas Based on Ride-Hailing Trajectories
Urban planning and function layout have important implications for the journeys of a large percentage of commuters, which often make up the majority of daily traffic in many cities. Therefore, the analysis and forecast of traffic flow among urban functional areas are of great significance for detecting urban traffic flow directions and traffic congestion causes, as well as helping commuters plan routes in advance. Existing methods based on ride-h…
Computer Science (4 works) · Artificial Intelligence (3 works) · Automated Road and Building Extraction (3 works) · Engineering (3 works) · Data mining (2 works) · Global Positioning System (2 works) · Human Mobility and Location-Based Analysis (2 works) · Traffic congestion (2 works) · Traffic Prediction and Management Techniques (2 works) · Transport engineering (2 works)