Xiaoling Ye
Impact in
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- Forecasting Techniques and Applications
- Stock Market Forecasting Methods
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- Energy Load and Power Forecasting
- Advancements in Battery Materials
Papers in
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- Remote Sensing and LiDAR Applications 3
- Hydrological Forecasting Using AI 3
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- Energy Load and Power Forecasting 7
- Advanced Battery Materials and Technologies 3
- Advanced Semiconductor Detectors and Materials 3
- Co-authors
- Yingchao Zhang (6 shared papers)Min Xia (3 shared papers)Liguo Weng (2 shared papers)Tao Li (1 shared paper)Xiong Xiong (15 shared papers)Xiaoxiao Zheng (8 shared papers)Wencheng Liu (7 shared papers)Hu Li (8 shared papers)
In The Last Decade
Xiaoling Ye
53 papers receiving 540 citations
Peers
Comparison fields: 5 of 96
- Management Science and Operations Research 60
- Electrical and Electronic Engineering 241
- Materials Chemistry 146
- Electronic, Optical and Magnetic Materials 57
- Artificial Intelligence 86
Countries citing papers authored by Xiaoling Ye
This map shows the geographic impact of Xiaoling Ye'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 Xiaoling Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoling Ye more than expected).
Fields of papers citing papers by Xiaoling Ye
This network shows the impact of papers produced by Xiaoling Ye. 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 Xiaoling Ye. The network helps show where Xiaoling Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoling Ye, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 91 | |
| 2 | 2022 | 53 | |
| 3 | 2023 | 51 | |
| 4 | 2009 | 37 | |
| 5 | 2021 | 30 | |
| 6 | 2024 | 23 | |
| 7 | 1999 | 22 | |
| 8 | 2023 | 20 | |
| 9 | 2023 | 19 | |
| 10 | 2024 | 19 | |
| 11 | 2023 | 16 | |
| 12 | 2024 | 15 | |
| 13 | 2024 | 15 | |
| 14 | 2024 | 15 | |
| 15 | 2025 | 10 | |
| 16 | 2023 | 9 | |
| 17 | 2021 | 7 | |
| 18 | 2024 | 7 | |
| 19 | 2010 | 7 | |
| 20 | 2013 | 6 |
About Xiaoling Ye
Xiaoling Ye is a scholar working on Environmental Engineering, Electrical and Electronic Engineering, Management Science and Operations Research, Computer Vision and Pattern Recognition and Materials Chemistry, having authored 58 papers that have together received 557 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (7 papers), Semiconductor Quantum Structures and Devices (6 papers), Advanced Neural Network Applications (3 papers), Remote Sensing and LiDAR Applications (3 papers), Advanced Battery Materials and Technologies (3 papers), Advanced Semiconductor Detectors and Materials (3 papers), Hydrological Forecasting Using AI (3 papers) and Data Management and Algorithms (3 papers). The work is most often cited by research in Management Science and Operations Research (60 citations), Electrical and Electronic Engineering (241 citations), Materials Chemistry (146 citations), Electronic, Optical and Magnetic Materials (57 citations) and Artificial Intelligence (86 citations). Xiaoling Ye has collaborated with scholars based in China, Australia and Pakistan. Frequent co-authors include Yingchao Zhang, Min Xia, Liguo Weng, Tao Li, Xiong Xiong, Xiaoxiao Zheng, Wencheng Liu, Hu Li, Hassan Jafri and Mingyang Wang. Their work appears in journals such as Energy, International Journal of Remote Sensing, Chinese Physics Letters, Journal of Electron Spectroscopy and Related Phenomena and AIP Advances.
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.