Hai‐Kun Wang
- Electrical and Electronic Engineering top 10%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Management Science and Operations Research top 10%
- Co-authors
- Yitao LiuJ.-C. PengKe SongYi ChengCheng YiYan‐Feng LiChin‐Hui LeeHong‐Zhong Huang
- Topics
- Reliability and Maintenance Optimization (6 papers)Energy Load and Power Forecasting (5 papers)Advanced Battery Technologies Research (4 papers)
- Cited by
- Energy Engineering and Power TechnologyArtificial IntelligenceElectrical and Electronic Engineering
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Hai‐Kun Wang
27 papers receiving 612 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Electrical and Electronic Engineering 376
- Artificial Intelligence 222
- Control and Systems Engineering 90
- Aerospace Engineering 83
- Management Science and Operations Research 75
Countries citing papers authored by Hai‐Kun Wang
This map shows the geographic impact of Hai‐Kun Wang'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 Hai‐Kun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai‐Kun Wang more than expected).
Fields of papers citing papers by Hai‐Kun Wang
This network shows the impact of papers produced by Hai‐Kun Wang. 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 Hai‐Kun Wang. The network helps show where Hai‐Kun Wang may publish in the future.
Co-authorship network of co-authors of Hai‐Kun Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Hai‐Kun Wang. A scholar is included among the top collaborators of Hai‐Kun Wang 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 Hai‐Kun Wang. Hai‐Kun Wang 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 | 0 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 7 | |
| 10 | 0 | |
| 11 | 4 | |
| 12 | 2 | |
| 13 | 1 | |
| 14 | 6 | |
| 15 | 1 | |
| 16 | 0 | |
| 17 | 14 | |
| 18 | Deep belief network based deterministic and probabilistic wind speed forecasting approachbreakdown → | 430 |
| 19 | 9 | |
| 20 | 2 |
About Hai‐Kun Wang
Hai‐Kun Wang is a scholar working on Safety, Risk, Reliability and Quality, Statistics, Probability and Uncertainty and Signal Processing, having authored 32 papers that have together received 637 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (6 papers), Energy Load and Power Forecasting (5 papers) and Advanced Battery Technologies Research (4 papers). The work is most often cited by research in Energy Engineering and Power Technology (32 citations), Artificial Intelligence (222 citations) and Electrical and Electronic Engineering (376 citations). Hai‐Kun Wang has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Yitao Liu, J.-C. Peng, Ke Song, Yi Cheng, Cheng Yi, Yan‐Feng Li, Chin‐Hui Lee, Hong‐Zhong Huang, Yuan‐Jian Yang and Jingdong Chen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Scientific Reports and Applied Energy.
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.