Mingchen Li
Biographic Data
| ID | 6304632 |
|---|---|
| NAME | Mingchen Li |
| GIVEN NAMES | Mingchen |
| FAMILY NAME | Li |
| SIGNATURE | LI M |
| AFFILIATIONS | China University of Mining and Technology |
| ORCID | 0000-0002-0736-1541 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 9 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Spatio-temporal forecasting of tourism demand using graph Wavenet
A novel deep learning approach for tourism volume forecasting with tourist search data
Tourism volume forecasting is the hot topic in tourism management, and deep learning techniques as the promising tool are becoming popular for capturing the characteristics of tourism volume data, which is reflected in two aspects: data dimension reduction (i.e., stacked autoencoders [SAE]) and model forecasting (i.e., bi‐directional gated recurrent unit neural network [Bi‐GRU]). With Hong Kong inbound arrivals as a case, this study has empirical…
Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid Covid-19? Mixed-data sampling approach
A novel deep learning approach for tourism volume forecasting with tourist search data
Tourism volume forecasting is the hot topic in tourism management, and deep learning techniques as the promising tool are becoming popular for capturing the characteristics of tourism volume data, which is reflected in two aspects: data dimension reduction (i.e., stacked autoencoders [SAE]) and model forecasting (i.e., bi‐directional gated recurrent unit neural network [Bi‐GRU]). With Hong Kong inbound arrivals as a case, this study has empirical…
Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid Covid-19? Mixed-data sampling approach
Spatio-temporal forecasting of tourism demand using graph Wavenet
Diverse Aspects of Tourism Research (3 works) · Tourism (3 works) · Cartography (2 works) · Computer Science (2 works) · Geography (2 works) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Benchmark (surveying (1 work) · Business (1 work) · China (1 work)