Hao‐Chin Chang
- Control and Systems Engineering top 5%
- Industrial and Manufacturing Engineering top 2%
- Computer Networks and Communications top 10%
- Artificial Intelligence
- Electrical and Electronic Engineering
- Co-authors
- Tung-Kuan LiuChang‐Hua LienKer‐Wei YuJyh‐Horng ChouJenq-Der ChenYi‐You HouChien‐Yu HuangLong‐Yeu Chung
- Topics
- Stability and Control of Uncertain Systems (22 papers)Neural Networks Stability and Synchronization (18 papers)Adaptive Control of Nonlinear Systems (7 papers)
In The Last Decade
Hao‐Chin Chang
34 papers receiving 392 citations
Peers
Comparison fields: 5 of 44
- Control and Systems Engineering 169
- Industrial and Manufacturing Engineering 167
- Computer Networks and Communications 121
- Artificial Intelligence 60
- Electrical and Electronic Engineering 42
Countries citing papers authored by Hao‐Chin Chang
This map shows the geographic impact of Hao‐Chin Chang'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 Hao‐Chin Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao‐Chin Chang more than expected).
Fields of papers citing papers by Hao‐Chin Chang
This network shows the impact of papers produced by Hao‐Chin Chang. 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 Hao‐Chin Chang. The network helps show where Hao‐Chin Chang may publish in the future.
Co-authorship network of co-authors of Hao‐Chin Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Hao‐Chin Chang. A scholar is included among the top collaborators of Hao‐Chin Chang 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 Hao‐Chin Chang. Hao‐Chin Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 6 | |
| 10 | 13 | |
| 11 | 4 | |
| 12 | 9 | |
| 13 | 10 | |
| 14 | 6 | |
| 15 | 13 | |
| 16 | 14 | |
| 17 | 39 | |
| 18 | 1 | |
| 19 | 4 | |
| 20 | 10 |
About Hao‐Chin Chang
Hao‐Chin Chang is a scholar working on Control and Systems Engineering, Computer Networks and Communications and Energy Engineering and Power Technology, having authored 37 papers that have together received 399 indexed citations. Recurring topics across this work include Stability and Control of Uncertain Systems (22 papers), Neural Networks Stability and Synchronization (18 papers) and Adaptive Control of Nonlinear Systems (7 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (167 citations), Control and Systems Engineering (169 citations) and Computer Networks and Communications (121 citations). Hao‐Chin Chang has collaborated with scholars based in Taiwan, Yemen and India. Frequent co-authors include Tung-Kuan Liu, Chang‐Hua Lien, Ker‐Wei Yu, Jyh‐Horng Chou, Jenq-Der Chen, Yi‐You Hou, Chien‐Yu Huang, Long‐Yeu Chung, Yuan-Chih Chang and Berlin Chen. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Journal of the Franklin Institute.
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.