Hongwei Dai
- Artificial Intelligence top 5%
- Renewable Energy, Sustainability and the Environment
- Computational Theory and Mathematics top 5%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 10%
- Co-authors
- Shangce GaoJiujun ChengKaiyu WangSichen TaoTing JinYang YuJian SunJiahai Wang
- Topics
- Metaheuristic Optimization Algorithms Research (14 papers)Artificial Immune Systems Applications (10 papers)Evolutionary Algorithms and Applications (6 papers)
- Cited by
- Artificial IntelligenceRenewable Energy, Sustainability and the EnvironmentComputational Theory and Mathematics
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Hongwei Dai
25 papers receiving 538 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 357
- Renewable Energy, Sustainability and the Environment 102
- Computational Theory and Mathematics 99
- Electrical and Electronic Engineering 88
- Computer Networks and Communications 82
Countries citing papers authored by Hongwei Dai
This map shows the geographic impact of Hongwei Dai'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 Hongwei Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongwei Dai more than expected).
Fields of papers citing papers by Hongwei Dai
This network shows the impact of papers produced by Hongwei Dai. 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 Hongwei Dai. The network helps show where Hongwei Dai may publish in the future.
Co-authorship network of co-authors of Hongwei Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Hongwei Dai. A scholar is included among the top collaborators of Hongwei Dai 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 Hongwei Dai. Hongwei Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 19 | |
| 3 | 15 | |
| 4 | 22 | |
| 5 | 185 | |
| 6 | 18 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 63 | |
| 10 | 17 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 0 | |
| 14 | 2 | |
| 15 | 3 | |
| 16 | 14 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | Annealing Chaotic Pattern Search Learning Method for Multi- layer Neural Networks | 3 |
| 20 | 2 |
About Hongwei Dai
Hongwei Dai is a scholar working on Artificial Intelligence, Energy Engineering and Power Technology and Computational Theory and Mathematics, having authored 29 papers that have together received 562 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (14 papers), Artificial Immune Systems Applications (10 papers) and Evolutionary Algorithms and Applications (6 papers). The work is most often cited by research in Artificial Intelligence (357 citations), Renewable Energy, Sustainability and the Environment (102 citations) and Computational Theory and Mathematics (99 citations). Hongwei Dai has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Shangce Gao, Jiujun Cheng, Kaiyu Wang, Sichen Tao, Ting Jin, Yang Yu, Jian Sun, Jiahai Wang, MengChu Zhou and Minghua Ma. Their work appears in journals such as Expert Systems with Applications, Energy Conversion and Management and IEEE Access.
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.