Tunhua Wu
About
In The Last Decade
Tunhua Wu
57 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Environmental Engineering 627
- Water Science and Technology 626
- Artificial Intelligence 198
- Global and Planetary Change 198
- Electrical and Electronic Engineering 180
Countries citing papers authored by Tunhua Wu
This map shows the geographic impact of Tunhua Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tunhua Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tunhua Wu more than expected).
Fields of papers citing papers by Tunhua Wu
This network shows the impact of papers produced by Tunhua Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tunhua Wu. The network helps show where Tunhua Wu may publish in the future.
Co-authorship network of co-authors of Tunhua Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Tunhua Wu. A scholar is included among the top collaborators of Tunhua Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tunhua Wu. Tunhua Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 52 | |
| 10 | A deep learning interpretable model for river dissolved oxygen multi-step and interval prediction based on multi-source data fusion breakdown → | 86 |
| 11 | 44 | |
| 12 | 15 | |
| 13 | An ensemble CNN-LSTM and GRU adaptive weighting model based improved sparrow search algorithm for predicting runoff using historical meteorological and runoff data as input breakdown → | 122 |
| 14 | 36 | |
| 15 | 2 | |
| 16 | 4 | |
| 17 | 25 | |
| 18 | 7 | |
| 19 | 7 | |
| 20 | 17 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.