Ran Ran
Impact in
-
- Photovoltaic System Optimization Techniques
- Artificial Intelligence top 10%
- Solar Radiation and Photovoltaics
Papers in
-
- Domain Adaptation and Few-Shot Learning 2
- Solar Radiation and Photovoltaics 2
-
- Advanced Neural Network Applications 4
- Co-authors
- Jidong Wang (3 shared papers)Yue Zhou (2 shared papers)Yanbo Che (1 shared paper)Jiawen Sun (1 shared paper)Chunna Tian (6 shared papers)Heng Zhou (6 shared papers)Zhenxi Zhang (4 shared papers)Zhicheng Jiao (2 shared papers)
- Journals
- Frontiers in Oncology (2 papers)Applied Sciences (2 papers)Signal Processing (1 paper)Translational Oncology (1 paper)Computers in Biology and Medicine (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Ran Ran
19 papers receiving 418 citations
Peers
Comparison fields: 5 of 88
- Renewable Energy, Sustainability and the Environment 134
- Artificial Intelligence 223
- Energy Engineering and Power Technology 14
- Electrical and Electronic Engineering 197
- Neurology 19
Countries citing papers authored by Ran Ran
This map shows the geographic impact of Ran Ran'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 Ran Ran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ran Ran more than expected).
Fields of papers citing papers by Ran Ran
This network shows the impact of papers produced by Ran Ran. 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 Ran Ran. The network helps show where Ran Ran may publish in the future.
Co-authors
The 25 scholars most cited alongside Ran Ran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 200 | |
| 2 | 2020 | 49 | |
| 3 | 2017 | 44 | |
| 4 | 2017 | 33 | |
| 5 | 2023 | 28 | |
| 6 | 2012 | 18 | |
| 7 | 2024 | 12 | |
| 8 | 2022 | 9 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 7 | |
| 11 | 2018 | 5 | |
| 12 | 2024 | 4 | |
| 13 | 2024 | 4 | |
| 14 | 2023 | 3 | |
| 15 | 2020 | 2 | |
| 16 | 2022 | 1 | |
| 17 | 2020 | 1 | |
| 18 | 2021 | 1 | |
| 19 | 2020 | 1 | |
| 20 | 2025 | 0 |
About Ran Ran
Ran Ran is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Pulmonary and Respiratory Medicine and Information Systems and Management, having authored 22 papers that have together received 429 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (4 papers), Advanced Neural Network Applications (4 papers), Brain Tumor Detection and Classification (2 papers), Photovoltaic System Optimization Techniques (2 papers), Advanced Breast Cancer Therapies (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Solar Radiation and Photovoltaics (2 papers) and Medical Imaging and Analysis (2 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (134 citations), Artificial Intelligence (223 citations), Energy Engineering and Power Technology (14 citations), Electrical and Electronic Engineering (197 citations) and Neurology (19 citations). Ran Ran has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jidong Wang, Yue Zhou, Yanbo Che, Jiawen Sun, Chunna Tian, Heng Zhou, Zhenxi Zhang, Zhicheng Jiao, Xiaomin Xu and Yubo Chen. Their work appears in journals such as Frontiers in Oncology, Applied Sciences, Signal Processing, Translational Oncology and Computers in Biology and Medicine.
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.