Lian Yan
Impact in
-
- Chaos control and synchronization
- Marketing top 10%
- Customer churn and segmentation
Papers in
-
- Neural Networks and Applications 3
- Neural Networks and Reservoir Computing 3
-
- Optical Network Technologies 6
- Semiconductor Lasers and Optical Devices 6
- Co-authors
- Richard H. Wolniewicz (4 shared papers)Robert H. Dodier (3 shared papers)Michael C. Mozer (2 shared papers)Bin Luo (12 shared papers)Xi Hua Zou (8 shared papers)Shui Ying Xiang (9 shared papers)David J. Miller (5 shared papers)Wei Pan (3 shared papers)
- Journals
- IEEE Journal of Quantum Electronics (3 papers)IEEE Photonics Technology Letters (3 papers)IEEE Journal of Selected Topics in Quantum Electronics (2 papers)Neurocomputing (1 paper)Neural Computation (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Lian Yan
25 papers receiving 485 citations
Peers
Comparison fields: 5 of 68
- Statistical and Nonlinear Physics 121
- Marketing 80
- Artificial Intelligence 232
- Computer Networks and Communications 135
- Electrical and Electronic Engineering 186
Countries citing papers authored by Lian Yan
This map shows the geographic impact of Lian Yan'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 Lian Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lian Yan more than expected).
Fields of papers citing papers by Lian Yan
This network shows the impact of papers produced by Lian Yan. 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 Lian Yan. The network helps show where Lian Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Lian Yan, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Optimizing classifier performance via an approximation to the Wilcoxon-Mann-Whitney statistic | 2003 | 131 |
| 2 | 2012 | 76 | |
| 3 | 2004 | 52 | |
| 4 | 2010 | 42 | |
| 5 | 1999 | 27 | |
| 6 | 2002 | 25 | |
| 7 | 2011 | 23 | |
| 8 | 2011 | 22 | |
| 9 | 2006 | 19 | |
| 10 | 2012 | 19 | |
| 11 | 2012 | 18 | |
| 12 | 2011 | 16 | |
| 13 | 2004 | 14 | |
| 14 | 2012 | 14 | |
| 15 | 2000 | 10 | |
| 16 | 2009 | 6 | |
| 17 | 2006 | 5 | |
| 18 | 2004 | 5 | |
| 19 | 2024 | 3 | |
| 20 | 2013 | 3 |
About Lian Yan
Lian Yan is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Statistical and Nonlinear Physics and Marketing, having authored 26 papers that have together received 537 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (6 papers), Optical Network Technologies (6 papers), Semiconductor Lasers and Optical Devices (6 papers), Customer churn and segmentation (6 papers), Chaos control and synchronization (5 papers), Data Mining Algorithms and Applications (4 papers), Neural Networks and Applications (3 papers) and Neural Networks and Reservoir Computing (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (121 citations), Marketing (80 citations), Artificial Intelligence (232 citations), Computer Networks and Communications (135 citations) and Electrical and Electronic Engineering (186 citations). Lian Yan has collaborated with scholars based in China and United States. Frequent co-authors include Richard H. Wolniewicz, Robert H. Dodier, Michael C. Mozer, Bin Luo, Xi Hua Zou, Shui Ying Xiang, David J. Miller, Wei Pan, Ning Jiang and Wei Pan. Their work appears in journals such as IEEE Journal of Quantum Electronics, IEEE Photonics Technology Letters, IEEE Journal of Selected Topics in Quantum Electronics, Neurocomputing and Neural Computation.
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.