Lifeng Gao
Biographic Data
| ID | 7755224 |
|---|---|
| NAME | Lifeng Gao |
| GIVEN NAMES | Lifeng |
| FAMILY NAME | Gao |
| SIGNATURE | GAO L |
| AFFILIATIONS | Shanghai Jiao Tong University |
| ORCID | 0009-0005-3308-1825 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Grid Partition-Based Dynamic Spatial–Temporal Graph Convolutional Network for Large-Scale Traffic Flow Forecasting
Accurate forecasting of city-level large-scale traffic flow is crucial for efficient traffic management and effective transport planning. However, previously proposed traffic flow prediction methods model dynamic spatial correlations across entire traffic networks, leading to high computational complexity, elevated memory usage, and model overfitting. Therefore, a novel grid partition-based dynamic spatial–temporal graph convolutional network was…
Residential mobility and liver cancer risk
The possible association between residential mobility and a higher risk of liver cancer in women could suggest the need for effective interventions to reduce adverse environmental exposures and enhance people's health
No prominent works on this page.
Residential mobility and liver cancer risk
The possible association between residential mobility and a higher risk of liver cancer in women could suggest the need for effective interventions to reduce adverse environmental exposures and enhance people's health
Grid Partition-Based Dynamic Spatial–Temporal Graph Convolutional Network for Large-Scale Traffic Flow Forecasting
Accurate forecasting of city-level large-scale traffic flow is crucial for efficient traffic management and effective transport planning. However, previously proposed traffic flow prediction methods model dynamic spatial correlations across entire traffic networks, leading to high computational complexity, elevated memory usage, and model overfitting. Therefore, a novel grid partition-based dynamic spatial–temporal graph convolutional network was…
Air Quality and Health Impacts (1 work) · Biostatistics (1 work) · Cancer (1 work) · Cohort study (1 work) · Computer Science (1 work) · Confidence interval (1 work) · Data mining (1 work) · Demography (1 work) · Demography (1 work) · Environmental health (1 work)