K.E. ArunKumar
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
Papers in
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- COVID-19 epidemiological studies 3
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- COVID-19 diagnosis using AI 2
- Co-authors
- Dinesh V. Kalaga (4 shared papers)Masahiro Kawaji (4 shared papers)Ch. Mohan Sai Kumar (3 shared papers)Timothy M. Brenza (3 shared papers)Govinda Chilkoor (2 shared papers)Bharat K. Jasthi (1 shared paper)Meyya Meyyappan (1 shared paper)Grigoriy A. Sereda (1 shared paper)
- Journals
- Alexandria Engineering Journal (1 paper)Chaos Solitons & Fractals (1 paper)Chemical Engineering Journal (1 paper)Applied Soft Computing (1 paper)Carbon (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
K.E. ArunKumar
7 papers receiving 560 citations
K.E. ArunKumar's Hit Papers
Peers
Comparison fields: 5 of 116
- Modeling and Simulation 98
- Management Science and Operations Research 86
- Health Informatics 6
- Radiology, Nuclear Medicine and Imaging 84
- Artificial Intelligence 139
Countries citing papers authored by K.E. ArunKumar
This map shows the geographic impact of K.E. ArunKumar'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 K.E. ArunKumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K.E. ArunKumar more than expected).
Fields of papers citing papers by K.E. ArunKumar
This network shows the impact of papers produced by K.E. ArunKumar. 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 K.E. ArunKumar. The network helps show where K.E. ArunKumar may publish in the future.
Co-authors
The 14 scholars most cited alongside K.E. ArunKumar, 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 | Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal autoregressive Integrated moving average (SARIMA) for forecasting COVID-19 trends Hit paper breakdown → | 2022 | 183 |
| 2 | 2021 | 175 | |
| 3 | 2021 | 153 | |
| 4 | 2019 | 52 | |
| 5 | 2019 | 15 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 |
About K.E. ArunKumar
K.E. ArunKumar is a scholar working on Modeling and Simulation, Radiology, Nuclear Medicine and Imaging, Economics and Econometrics, Polymers and Plastics and Mechanical Engineering, having authored 7 papers that have together received 580 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (3 papers), COVID-19 diagnosis using AI (2 papers), COVID-19 Pandemic Impacts (2 papers), Anomaly Detection Techniques and Applications (1 paper), Mobile Health and mHealth Applications (1 paper), Asphalt Pavement Performance Evaluation (1 paper), Concrete Corrosion and Durability (1 paper) and Innovative Microfluidic and Catalytic Techniques Innovation (1 paper). The work is most often cited by research in Modeling and Simulation (98 citations), Management Science and Operations Research (86 citations), Health Informatics (6 citations), Radiology, Nuclear Medicine and Imaging (84 citations) and Artificial Intelligence (139 citations). K.E. ArunKumar has collaborated with scholars based in United States and India. Frequent co-authors include Dinesh V. Kalaga, Masahiro Kawaji, Ch. Mohan Sai Kumar, Timothy M. Brenza, Govinda Chilkoor, Bharat K. Jasthi, Meyya Meyyappan, Grigoriy A. Sereda, Venkataramana R. Gadhamshetty and Nikhil A. Koratkar. Their work appears in journals such as Alexandria Engineering Journal, Chaos Solitons & Fractals, Chemical Engineering Journal, Applied Soft Computing and Carbon.
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.