Xiaoxia Qi
Impact in
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- Photovoltaic System Optimization Techniques
Papers in
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- Advanced materials and composites 17
- High Entropy Alloys Studies 9
- Additive Manufacturing Materials and Processes 4
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- High-Temperature Coating Behaviors 11
- Co-authors
- Hongda Liu (5 shared papers)Kejun Wang (3 shared papers)Fangyi Li (21 shared papers)Yanle Li (20 shared papers)Yang Zhao (4 shared papers)Zenghe Li (4 shared papers)Haiyang Lu (9 shared papers)Lu Fang (1 shared paper)
In The Last Decade
Xiaoxia Qi
43 papers receiving 1.5k citations
Xiaoxia Qi's Hit Papers
Peers
Comparison fields: 5 of 95
- Energy Engineering and Power Technology 98
- Renewable Energy, Sustainability and the Environment 466
- Artificial Intelligence 676
- Electrical and Electronic Engineering 914
- Management Science and Operations Research 121
Countries citing papers authored by Xiaoxia Qi
This map shows the geographic impact of Xiaoxia Qi'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 Xiaoxia Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoxia Qi more than expected).
Fields of papers citing papers by Xiaoxia Qi
This network shows the impact of papers produced by Xiaoxia Qi. 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 Xiaoxia Qi. The network helps show where Xiaoxia Qi may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoxia Qi, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network Hit paper breakdown → | 2019 | 418 |
| 2 | Photovoltaic power forecasting based LSTM-Convolutional Network Hit paper breakdown → | 2019 | 363 |
| 3 | 2018 | 247 | |
| 4 | 2017 | 63 | |
| 5 | 2017 | 54 | |
| 6 | 2023 | 38 | |
| 7 | 2016 | 33 | |
| 8 | 2020 | 32 | |
| 9 | 2020 | 32 | |
| 10 | 2018 | 30 | |
| 11 | 2017 | 21 | |
| 12 | 2023 | 20 | |
| 13 | 2023 | 20 | |
| 14 | 2021 | 19 | |
| 15 | 2021 | 17 | |
| 16 | 1987 | 16 | |
| 17 | 2019 | 14 | |
| 18 | 2018 | 13 | |
| 19 | 2024 | 12 | |
| 20 | 2024 | 10 |
About Xiaoxia Qi
Xiaoxia Qi is a scholar working on Mechanical Engineering, Aerospace Engineering, Electrical and Electronic Engineering, Materials Chemistry and Mechanics of Materials, having authored 49 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced materials and composites (17 papers), High-Temperature Coating Behaviors (11 papers), High Entropy Alloys Studies (9 papers), Metal and Thin Film Mechanics (7 papers), Additive Manufacturing Materials and Processes (4 papers), Energy Load and Power Forecasting (4 papers), Advanced Malware Detection Techniques (3 papers) and Advanced Photocatalysis Techniques (3 papers). The work is most often cited by research in Energy Engineering and Power Technology (98 citations), Renewable Energy, Sustainability and the Environment (466 citations), Artificial Intelligence (676 citations), Electrical and Electronic Engineering (914 citations) and Management Science and Operations Research (121 citations). Xiaoxia Qi has collaborated with scholars based in China, Malaysia and Portugal. Frequent co-authors include Hongda Liu, Kejun Wang, Fangyi Li, Yanle Li, Yang Zhao, Zenghe Li, Haiyang Lu, Lu Fang, Sifang Li and Binbin Huang. Their work appears in journals such as Surface and Coatings Technology, Ceramics International, Journal of Alloys and Compounds, Journal of Materials Research and Technology and Electronics.
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.