Hao Su
- Control and Systems Engineering top 2%
- Mechanical Engineering top 10%
- Electrical and Electronic Engineering
- Mechanics of Materials top 10%
- Artificial Intelligence top 10%
- Topics
- Machine Fault Diagnosis Techniques (14 papers)Gear and Bearing Dynamics Analysis (7 papers)Energy Load and Power Forecasting (4 papers)
- Partner nations
- ChinaUnited KingdomMacao
In The Last Decade
Hao Su
17 papers receiving 878 citations
Hit Papers
Peers
Comparison fields: 5 of 63
- Control and Systems Engineering 679
- Mechanical Engineering 336
- Electrical and Electronic Engineering 206
- Mechanics of Materials 192
- Artificial Intelligence 163
Countries citing papers authored by Hao Su
This map shows the geographic impact of Hao Su'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 Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Su more than expected).
Fields of papers citing papers by Hao Su
This network shows the impact of papers produced by Hao Su. 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 Su. The network helps show where Hao Su may publish in the future.
Co-authorship network of co-authors of Hao Su
This figure shows the co-authorship network connecting the top 25 collaborators of Hao Su. A scholar is included among the top collaborators of Hao Su 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 Su. Hao Su 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 | 11 | |
| 3 | 34 | |
| 4 | 14 | |
| 5 | 1 | |
| 6 | 43 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 23 | |
| 11 | A novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditionsbreakdown → | 190 |
| 12 | 60 | |
| 13 | 20 | |
| 14 | 14 | |
| 15 | 30 | |
| 16 | Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networksbreakdown → | 167 |
| 17 | Fault detection of wind turbine based on SCADA data analysis using CNN and LSTM with attention mechanismbreakdown → | 277 |
| 18 | 13 | |
| 19 | 1 | |
| 20 | 12 |
About Hao Su
Hao Su is a scholar working on Control and Systems Engineering, Mechanical Engineering and Safety, Risk, Reliability and Quality, having authored 20 papers that have together received 912 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (14 papers), Gear and Bearing Dynamics Analysis (7 papers) and Energy Load and Power Forecasting (4 papers). The work is most often cited by research in Control and Systems Engineering (679 citations), Safety, Risk, Reliability and Quality (91 citations) and Mechanical Engineering (336 citations). Hao Su has collaborated with scholars based in China, United Kingdom and Macao. Frequent co-authors include Ling Xiang, Aijun Hu, Xin Yang, Penghe Wang, Yonggang Xu, Benfeng Gao, Yongfeng Yang, Weiyang Qin, Yue Zhang and Rui Yang. Their work appears in journals such as Applied Energy, Renewable Energy and Mechanical Systems and Signal Processing.
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.