Xiaofeng Yuan
- Control and Systems Engineering top 0.1%
- Mechanical Engineering top 0.5%
- Artificial Intelligence top 0.5%
- Analytical Chemistry top 0.5%
- Industrial and Manufacturing Engineering top 0.5%
- Topics
- Fault Detection and Control Systems (109 papers)Mineral Processing and Grinding (55 papers)Advanced Control Systems Optimization (44 papers)
In The Last Decade
Xiaofeng Yuan
130 papers receiving 5.8k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Control and Systems Engineering 4.4k
- Mechanical Engineering 2.0k
- Artificial Intelligence 1.8k
- Analytical Chemistry 678
- Industrial and Manufacturing Engineering 612
Countries citing papers authored by Xiaofeng Yuan
This map shows the geographic impact of Xiaofeng Yuan'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 Xiaofeng Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaofeng Yuan more than expected).
Fields of papers citing papers by Xiaofeng Yuan
This network shows the impact of papers produced by Xiaofeng Yuan. 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 Xiaofeng Yuan. The network helps show where Xiaofeng Yuan may publish in the future.
Co-authorship network of co-authors of Xiaofeng Yuan
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaofeng Yuan. A scholar is included among the top collaborators of Xiaofeng Yuan 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 Xiaofeng Yuan. Xiaofeng Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 0 | |
| 6 | 8 | |
| 7 | 12 | |
| 8 | 24 | |
| 9 | Quality Prediction Modeling for Industrial Processes Using Multiscale Attention-Based Convolutional Neural Networkbreakdown → | 60 |
| 10 | 8 | |
| 11 | 7 | |
| 12 | 29 | |
| 13 | 26 | |
| 14 | 17 | |
| 15 | 70 | |
| 16 | 32 | |
| 17 | 9 | |
| 18 | Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategybreakdown → | 231 |
| 19 | Fuzzy C-means Cluster Based on Local Weighted Principal Component Regression for Soft Sensor of an Industrial Hydrocracking process | 1 |
| 20 | Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAEbreakdown → | 516 |
About Xiaofeng Yuan
Xiaofeng Yuan is a scholar working on Control and Systems Engineering, Analytical Chemistry and Mechanical Engineering, having authored 140 papers that have together received 6.0k indexed citations. Recurring topics across this work include Fault Detection and Control Systems (109 papers), Mineral Processing and Grinding (55 papers) and Advanced Control Systems Optimization (44 papers). The work is most often cited by research in Control and Systems Engineering (4.4k citations), Analytical Chemistry (678 citations) and Industrial and Manufacturing Engineering (612 citations). Xiaofeng Yuan has collaborated with scholars based in China, Hong Kong and Germany. Frequent co-authors include Yalin Wang, Chunhua Yang, Weihua Gui, Lin Li, Weihua Gui, Zhiqiang Ge, Biao Huang, Zhihuan Song, Kai Wang and Lingjian Ye. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications 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.