Ye Ren
- Electrical and Electronic Engineering top 5%
- Artificial Intelligence top 1%
- Management Science and Operations Research top 1%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 5%
- Co-authors
- Ponnuthurai Nagaratnam SuganthanLe ZhangNarasimalu SrikanthG.A.J. AmaratungaXueheng QiuN. V. SrikanthDipak LahaYinhua Liu
- Topics
- Energy Load and Power Forecasting (12 papers)Neural Networks and Applications (6 papers)Machine Fault Diagnosis Techniques (5 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceEnergy Engineering and Power Technology
- Journals
- Renewable and Sustainable Energy ReviewsExpert Systems with ApplicationsInformation Sciences
- Partner nations
- SingaporeChinaUnited Kingdom
In The Last Decade
Ye Ren
28 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Electrical and Electronic Engineering 1.3k
- Artificial Intelligence 899
- Management Science and Operations Research 451
- Computer Vision and Pattern Recognition 294
- Control and Systems Engineering 293
Countries citing papers authored by Ye Ren
This map shows the geographic impact of Ye Ren'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 Ye Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ye Ren more than expected).
Fields of papers citing papers by Ye Ren
This network shows the impact of papers produced by Ye Ren. 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 Ye Ren. The network helps show where Ye Ren may publish in the future.
Co-authorship network of co-authors of Ye Ren
This figure shows the co-authorship network connecting the top 25 collaborators of Ye Ren. A scholar is included among the top collaborators of Ye Ren 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 Ye Ren. Ye Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | 229 | |
| 8 | 17 | |
| 9 | 6 | |
| 10 | Ensemble methods for wind and solar power forecasting—A state-of-the-art reviewbreakdown → | 335 |
| 11 | 1 | |
| 12 | 22 | |
| 13 | 273 | |
| 14 | 178 | |
| 15 | 259 | |
| 16 | 16 | |
| 17 | 5 | |
| 18 | 11 | |
| 19 | Empirical comparison of bagging-based ensemble classifiers | 8 |
| 20 | 3 |
About Ye Ren
Ye Ren is a scholar working on Artificial Intelligence, Management Science and Operations Research and Electrical and Electronic Engineering, having authored 31 papers that have together received 2.4k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (12 papers), Neural Networks and Applications (6 papers) and Machine Fault Diagnosis Techniques (5 papers). The work is most often cited by research in Management Science and Operations Research (451 citations), Artificial Intelligence (899 citations) and Energy Engineering and Power Technology (73 citations). Ye Ren has collaborated with scholars based in Singapore, China and United Kingdom. Frequent co-authors include Ponnuthurai Nagaratnam Suganthan, Le Zhang, Narasimalu Srikanth, G.A.J. Amaratunga, Xueheng Qiu, N. V. Srikanth, Dipak Laha, Yinhua Liu, Soham Sarkar and Chunyu Peng. Their work appears in journals such as Renewable and Sustainable Energy Reviews, Expert Systems with Applications and Information Sciences.
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.