Kumar Kannan

460 total citations
13 papers, 281 citations indexed

About

Kumar Kannan is a scholar working on Management Science and Operations Research, Information Systems and Artificial Intelligence. According to data from OpenAlex, Kumar Kannan has authored 13 papers receiving a total of 281 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Management Science and Operations Research, 3 papers in Information Systems and 3 papers in Artificial Intelligence. Recurrent topics in Kumar Kannan's work include Stock Market Forecasting Methods (5 papers), Complex Systems and Time Series Analysis (3 papers) and Energy Load and Power Forecasting (2 papers). Kumar Kannan is often cited by papers focused on Stock Market Forecasting Methods (5 papers), Complex Systems and Time Series Analysis (3 papers) and Energy Load and Power Forecasting (2 papers). Kumar Kannan collaborates with scholars based in India, Hong Kong and China. Kumar Kannan's co-authors include Kamatchi Rajaram, S. N. Sivanandam, Arunkumar Thangavelu, M. Iyapparaja, Chunhua Su, Weizheng Wang, Siva Rama Krishnan Somayaji, Srinivas Koppu, M. Mohanraj and Liang Zhao and has published in prestigious journals such as Journal of Energy Storage, The Computer Journal and Computer Science Review.

In The Last Decade

Kumar Kannan

12 papers receiving 261 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Kumar Kannan India	7	179	99	55	51	47	13	281
Zhongcui Li China	7	162 0.9×	136 1.4×	50 0.9×	43 0.8×	56 1.2×	8	308
Jianfeng Si China	7	120 0.7×	25 0.3×	52 0.9×	41 0.8×	132 2.8×	13	282
Jinwen Sun China	9	60 0.3×	258 2.6×	23 0.4×	27 0.5×	24 0.5×	26	360
Umut Uğurlu Türkiye	9	88 0.5×	312 3.2×	47 0.9×	17 0.3×	33 0.7×	22	363
Jiahao Li China	8	29 0.2×	35 0.4×	12 0.2×	17 0.3×	58 1.2×	35	242
Ashkan Safari Iran	10	34 0.2×	160 1.6×	8 0.1×	5 0.1×	43 0.9×	43	267
Alejandro Fernández-Montes Spain	12	34 0.2×	68 0.7×	32 0.6×	19 0.4×	19 0.4×	26	375
G. Manikandan India	11	35 0.2×	42 0.4×	5 0.1×	8 0.2×	48 1.0×	29	218
H. Arango Brazil	10	28 0.2×	285 2.9×	19 0.3×	7 0.1×	25 0.5×	54	366

Countries citing papers authored by Kumar Kannan

Since Specialization

Citations

This map shows the geographic impact of Kumar Kannan'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 Kumar Kannan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kumar Kannan more than expected).

Fields of papers citing papers by Kumar Kannan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kumar Kannan. 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 Kumar Kannan. The network helps show where Kumar Kannan may publish in the future.

Co-authorship network of co-authors of Kumar Kannan

This figure shows the co-authorship network connecting the top 25 collaborators of Kumar Kannan. A scholar is included among the top collaborators of Kumar Kannan 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 Kumar Kannan. Kumar Kannan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

Kannan, Kumar, et al.. (2025). Federated Deep Learning for Cancer Diagnosis: Combining Heterogeneous Multi-Institutional Data Using GAN-Based Augmentation. 258–263.

Koppu, Srinivas, Kumar Kannan, Siva Rama Krishnan Somayaji, et al.. (2022). Fusion of Blockchain, IoT and Artificial Intelligence - A Survey. IEICE Transactions on Information and Systems. E105.D(2). 300–308. 11 indexed citations

Kannan, Kumar, et al.. (2021). Chronological penguin Adam-based deep long short-term memory classifier for stock market prediction. International Journal of Intelligent Information and Database Systems. 14(3). 215–215. 1 indexed citations

Kannan, Kumar, et al.. (2020). A comparative study of performance and emission characteristics of a diesel engine using various non-edible extracts. Progress in Industrial Ecology An International Journal. 14(2). 91–91. 2 indexed citations

Kannan, Kumar, et al.. (2020). Wrapper-Enabled Feature Selection and CPLM-Based NARX Model for Stock Market Prediction. The Computer Journal. 64(2). 169–184. 10 indexed citations

Kannan, Kumar & Kamatchi Rajaram. (2019). Augmented heat transfer by hybrid thermosyphon assisted thermal energy storage system for electronic cooling. Journal of Energy Storage. 27. 101146–101146. 23 indexed citations

Kannan, Kumar, et al.. (2019). Systematic analysis and review of stock market prediction techniques. Computer Science Review. 34. 100190–100190. 188 indexed citations

Kannan, Kumar, et al.. (2019). E-Commerce: Stock Market Analysis Blended With Mining and Ann. 1104–1108. 1 indexed citations

Kannan, Kumar, et al.. (2019). Ensemble Computations on Stock Market: A Standardized Review for Future Directions. 1–6. 4 indexed citations

10.

Kannan, Kumar, et al.. (2016). Sentimental Analysis of Twitter Data using Classifier Algorithms. International Journal of Electrical and Computer Engineering (IJECE). 6(1). 357–357. 11 indexed citations

11.

Kannan, Kumar, et al.. (2015). EXPERIMENTAL STUDY OF THE EFFECT OF FUEL INJECTION PRESSURE ON DIESEL ENGINE PERFORMANCE AND EMISSION. 10 indexed citations

12.

Kannan, Kumar, et al.. (2015). An approach for decomposing requirements into analysis pattern using problem frames (DRAP-PF). 47. 2392–2396. 1 indexed citations

13.

Thangavelu, Arunkumar, et al.. (2007). Location Identification and Vehicle Tracking using VANET ( VETRAC). 112–116. 19 indexed citations

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.

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