Prem Kumar Singh
Impact in
- Computational Theory and Mathematics top 0.5%
- Rough Sets and Fuzzy Logic
- Advanced Algebra and Logic
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- Multi-Criteria Decision Making
- Fuzzy and Soft Set Theory
Papers in
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- Rough Sets and Fuzzy Logic 48
- Advanced Algebra and Logic 13
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- Multi-Criteria Decision Making 35
- Co-authors
- Ch. Aswani Kumar (6 shared papers)Abdullah Gani (3 shared papers)Jinhai Li (2 shared papers)Aswani Kumar Cherukuri (3 shared papers)J. P. Tandon (2 shared papers)Ganeshsree Selvachandran (1 shared paper)Suleman Khan (1 shared paper)Said Broumi (5 shared papers)
In The Last Decade
Prem Kumar Singh
84 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 102
- Computational Theory and Mathematics 803
- Management Science and Operations Research 604
- Signal Processing 235
- Artificial Intelligence 532
- Information Systems 208
Countries citing papers authored by Prem Kumar Singh
This map shows the geographic impact of Prem Kumar Singh'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 Prem Kumar Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prem Kumar Singh more than expected).
Fields of papers citing papers by Prem Kumar Singh
This network shows the impact of papers produced by Prem Kumar Singh. 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 Prem Kumar Singh. The network helps show where Prem Kumar Singh may publish in the future.
Co-authors
The 25 scholars most cited alongside Prem Kumar Singh, 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 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 106 | |
| 2 | 2016 | 102 | |
| 3 | 2016 | 68 | |
| 4 | 2014 | 64 | |
| 5 | 2015 | 59 | |
| 6 | 2022 | 53 | |
| 7 | 2015 | 47 | |
| 8 | 2017 | 43 | |
| 9 | 1981 | 38 | |
| 10 | 2017 | 36 | |
| 11 | 2017 | 35 | |
| 12 | 2016 | 34 | |
| 13 | 2018 | 30 | |
| 14 | 2012 | 29 | |
| 15 | 2017 | 28 | |
| 16 | 2017 | 27 | |
| 17 | 2018 | 24 | |
| 18 | 2018 | 24 | |
| 19 | 2020 | 22 | |
| 20 | 2021 | 22 |
About Prem Kumar Singh
Prem Kumar Singh is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research, Artificial Intelligence, Signal Processing and Information Systems, having authored 88 papers that have together received 1.3k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (48 papers), Multi-Criteria Decision Making (35 papers), Fuzzy Logic and Control Systems (18 papers), Data Management and Algorithms (13 papers), Advanced Algebra and Logic (13 papers), Data Mining Algorithms and Applications (10 papers), Vaccine Coverage and Hesitancy (6 papers) and Cognitive Science and Mapping (6 papers). The work is most often cited by research in Computational Theory and Mathematics (803 citations), Management Science and Operations Research (604 citations), Signal Processing (235 citations), Artificial Intelligence (532 citations) and Information Systems (208 citations). Prem Kumar Singh has collaborated with scholars based in India, Malaysia and China. Frequent co-authors include Ch. Aswani Kumar, Abdullah Gani, Jinhai Li, Aswani Kumar Cherukuri, J. P. Tandon, Ganeshsree Selvachandran, Suleman Khan, Said Broumi, Ainuddin Wahid Abdul Wahab and Pritu Dhalaria. Their work appears in journals such as Granular Computing, Neural Processing Letters, International Journal of Machine Learning and Cybernetics, Soft Computing and Cognitive 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.