Ching-Chih Tai
About
In The Last Decade
Ching-Chih Tai
12 papers receiving 422 citations
Peers
Comparison fields: 5 of 50
- Mechanical Engineering 382
- Industrial and Manufacturing Engineering 249
- Automotive Engineering 113
- Computational Mechanics 79
- Biomedical Engineering 52
Countries citing papers authored by Ching-Chih Tai
This map shows the geographic impact of Ching-Chih Tai'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 Ching-Chih Tai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ching-Chih Tai more than expected).
Fields of papers citing papers by Ching-Chih Tai
This network shows the impact of papers produced by Ching-Chih Tai. 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 Ching-Chih Tai. The network helps show where Ching-Chih Tai may publish in the future.
Co-authorship network of co-authors of Ching-Chih Tai
This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Chih Tai. A scholar is included among the top collaborators of Ching-Chih Tai 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 Ching-Chih Tai. Ching-Chih Tai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Attention-Based Spatial-Temporal Graph Neural Network With Long-Term Dependencies for Traffic Speed Prediction | IEEE Transactions on Intelligent Transportation Systems | Ching-Chih Tai, Min-Te Sun et al. | 0 |
| 2 | The effective factors in the warpage problem of an injection-molded part with a thin shell feature | Journal of Materials Processing Technology | Ching-Chih Tai et al. | 260 |
| 3 | The processing of data points basing on design intent in reverse engineering | International Journal of Machine Tools and Manufacture | Ching-Chih Tai et al. | 38 |
| 4 | The Pre-Processing of Data Points for Curve Fitting in Reverse Engineering | The International Journal of Advanced Manufacturing Technology | Ching-Chih Tai et al. | 37 |
| 5 | The optimization accuracy control of a die-casting product part | Journal of Materials Processing Technology | Ching-Chih Tai | 9 |
| 6 | The Application of Neural Networks in the Prediction of Spring-back in an L-Shaped Bend | The International Journal of Advanced Manufacturing Technology | Jing-Chie Lin, Ching-Chih Tai | 13 |
| 7 | Accuracy Optimisation for Mould Surface Profile Milling | The International Journal of Advanced Manufacturing Technology | Jing-Chie Lin, Ching-Chih Tai | 16 |
| 8 | The optimal position for the injection gate of a die-casting die | Journal of Materials Processing Technology | Ching-Chih Tai, Jing-Chie Lin | 11 |
| 9 | The runner optimisation design of a die-casting die and the part produced | The International Journal of Advanced Manufacturing Technology | Jing-Chie Lin, Ching-Chih Tai | 4 |
| 10 | A runner-optimization design study of a die-casting die | Journal of Materials Processing Technology | Ching-Chih Tai, Jing-Chie Lin | 25 |
| 11 | The optimisation deep-draw clearance design for deep-draw dies | The International Journal of Advanced Manufacturing Technology | Ching-Chih Tai, Jing-Chie Lin | 5 |
| 12 | Model for cutting forces prediction in ball-end milling | International Journal of Machine Tools and Manufacture | Ching-Chih Tai, Kuang-Hua Fuh | 18 |
| 13 | The prediction of cutting forces in the ball-end milling process | Journal of Materials Processing Technology | Ching-Chih Tai, Kuang-Hua Fuh | 24 |
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.