Raghavendra Kumar
Impact in
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
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- Time Series Analysis and Forecasting
Papers in
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- Time Series Analysis and Forecasting 6
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- Stock Market Forecasting Methods 5
- Forecasting Techniques and Applications 2
- Co-authors
- Pardeep Kumar (6 shared papers)Yugal Kumar (5 shared papers)Jyotir Moy Chatterjee (1 shared paper)Sung Wook Baik (1 shared paper)Lê Hoàng Sơn (1 shared paper)Francisco Chiclana (1 shared paper)Mamta Mittal (1 shared paper)Manju Khari (2 shared papers)
- Journals
- Multimedia Tools and Applications (2 papers)Knowledge-Based Systems (1 paper)Neural Computing and Applications (1 paper)International Journal of Information Technology (1 paper)Advances in intelligent systems and computing (1 paper)
- Partner nations
- IndiaVietnamUnited Kingdom
In The Last Decade
Raghavendra Kumar
10 papers receiving 292 citations
Peers
Comparison fields: 5 of 95
- Management Science and Operations Research 95
- Signal Processing 37
- Environmental Engineering 42
- Artificial Intelligence 86
- Information Systems 46
Countries citing papers authored by Raghavendra Kumar
This map shows the geographic impact of Raghavendra Kumar'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 Raghavendra Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raghavendra Kumar more than expected).
Fields of papers citing papers by Raghavendra Kumar
This network shows the impact of papers produced by Raghavendra Kumar. 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 Raghavendra Kumar. The network helps show where Raghavendra Kumar may publish in the future.
Co-authors
The 13 scholars most cited alongside Raghavendra Kumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 88 | |
| 2 | 2020 | 81 | |
| 3 | 2021 | 46 | |
| 4 | 2021 | 26 | |
| 5 | 2021 | 24 | |
| 6 | 2021 | 23 | |
| 7 | 2022 | 19 | |
| 8 | 2023 | 2 | |
| 9 | 2018 | 2 | |
| 10 | 2020 | 2 | |
| 11 | 2019 | 1 |
About Raghavendra Kumar
Raghavendra Kumar is a scholar working on Signal Processing, Management Science and Operations Research, Artificial Intelligence, Health Information Management and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 314 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (6 papers), Stock Market Forecasting Methods (5 papers), Data Stream Mining Techniques (2 papers), Artificial Intelligence in Healthcare (2 papers), Forecasting Techniques and Applications (2 papers), Digital Imaging for Blood Diseases (1 paper), Evolutionary Algorithms and Applications (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Management Science and Operations Research (95 citations), Signal Processing (37 citations), Environmental Engineering (42 citations), Artificial Intelligence (86 citations) and Information Systems (46 citations). Raghavendra Kumar has collaborated with scholars based in India, Vietnam and United Kingdom. Frequent co-authors include Pardeep Kumar, Yugal Kumar, Jyotir Moy Chatterjee, Sung Wook Baik, Lê Hoàng Sơn, Francisco Chiclana, Mamta Mittal, Manju Khari, Arun Kumar Tripathi and Anjali Jain. Their work appears in journals such as Multimedia Tools and Applications, Knowledge-Based Systems, Neural Computing and Applications, International Journal of Information Technology and Advances in intelligent systems and computing.
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.