Fangrong Chang
Biographic Data
| ID | 7871467 |
|---|---|
| NAME | Fangrong Chang |
| GIVEN NAMES | Fangrong |
| FAMILY NAME | Chang |
| SIGNATURE | CHANG F |
| AFFILIATIONS | Central South University |
| ORCID | 0000-0002-0241-5838 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Impact of digitization and artificial intelligence on carbon emissions considering variable interaction and heterogeneity: An interpretable deep learning modeling framework
Carbon emission prediction of 275 cities in China considering artificial intelligence effects and feature interaction: A heterogeneous deep learning modeling framework
Injury Severity of Motorcycle Riders Involved in Traffic Crashes in Hunan, China: A Mixed Ordered Logit Approach
Issues related to motorcycle safety in China have not received enough research attention. As such, the causal relationship between injury outcomes of motorcycle crashes and potential risk factors remains unknown. This study intended to investigate the injury risk of motorcyclists involved in road traffic crashes in China. To account for the ordinal nature of response outcomes and unobserved heterogeneity, a mixed ordered logit model was employed.…
No prominent works on this page.
Injury Severity of Motorcycle Riders Involved in Traffic Crashes in Hunan, China: A Mixed Ordered Logit Approach
Issues related to motorcycle safety in China have not received enough research attention. As such, the causal relationship between injury outcomes of motorcycle crashes and potential risk factors remains unknown. This study intended to investigate the injury risk of motorcyclists involved in road traffic crashes in China. To account for the ordinal nature of response outcomes and unobserved heterogeneity, a mixed ordered logit model was employed.…
Carbon emission prediction of 275 cities in China considering artificial intelligence effects and feature interaction: A heterogeneous deep learning modeling framework
Impact of digitization and artificial intelligence on carbon emissions considering variable interaction and heterogeneity: An interpretable deep learning modeling framework
Computer Science (3 works) · Air Quality Monitoring and Forecasting (2 works) · Artificial Intelligence (2 works) · China (2 works) · Energy, Environment, Economic Growth (2 works) · Geography (2 works) · Machine learning (2 works) · Mathematics (2 works) · Algorithm (1 works) · Business (1 works)