R. Nedunchezhian

620 total citations
41 papers, 400 citations indexed

About

R. Nedunchezhian is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, R. Nedunchezhian has authored 41 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 18 papers in Information Systems and 7 papers in Computer Networks and Communications. Recurrent topics in R. Nedunchezhian's work include Data Mining Algorithms and Applications (11 papers), Rough Sets and Fuzzy Logic (7 papers) and Imbalanced Data Classification Techniques (6 papers). R. Nedunchezhian is often cited by papers focused on Data Mining Algorithms and Applications (11 papers), Rough Sets and Fuzzy Logic (7 papers) and Imbalanced Data Classification Techniques (6 papers). R. Nedunchezhian collaborates with scholars based in India, Nepal and United Kingdom. R. Nedunchezhian's co-authors include M. Rajalakshmi, P. Vivekanandan, G. V. Nagesh Kumar, B. Venkateswara Rao, Raj Bhatti, Sabuj Mallik, V. Ramanarayanan, N Lakshminarasamma, Kenny C. Otiaba and V. Vijayakumar and has published in prestigious journals such as IEEE Transactions on Computers, Journal of Network and Computer Applications and Artificial Intelligence Review.

In The Last Decade

R. Nedunchezhian

37 papers receiving 357 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Nedunchezhian India 11 132 132 130 84 49 41 400
Zhongyi Zhai China 8 111 0.8× 102 0.8× 200 1.5× 62 0.7× 24 0.5× 33 389
Man Qi United Kingdom 10 146 1.1× 185 1.4× 121 0.9× 80 1.0× 11 0.2× 58 419
Muhammad Sulaiman Pakistan 9 81 0.6× 142 1.1× 163 1.3× 33 0.4× 22 0.4× 19 354
Said Elnaffar United Arab Emirates 11 249 1.9× 124 0.9× 263 2.0× 40 0.5× 26 0.5× 50 418
Niranjan N. Chiplunkar India 10 114 0.9× 170 1.3× 89 0.7× 86 1.0× 21 0.4× 60 408
Adrián Pekár Hungary 11 75 0.6× 150 1.1× 271 2.1× 45 0.5× 14 0.3× 37 406
Tao Feng China 13 164 1.2× 173 1.3× 276 2.1× 48 0.6× 23 0.5× 93 531
Shakir Fattah Kak Iraq 13 281 2.1× 131 1.0× 201 1.5× 113 1.3× 12 0.2× 27 531
René Meier Ireland 12 108 0.8× 67 0.5× 376 2.9× 139 1.7× 36 0.7× 54 543

Countries citing papers authored by R. Nedunchezhian

Since Specialization
Citations

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

Fields of papers citing papers by R. Nedunchezhian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Nedunchezhian

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

All Works

20 of 20 papers shown
1.
Nedunchezhian, R., et al.. (2024). Cardiac abnormalities from 12‐Lead ECG signals prediction based on deep convolutional neural network optimized with nomadic people optimization algorithm. International Journal of Adaptive Control and Signal Processing. 38(4). 1136–1152. 4 indexed citations
2.
3.
Nedunchezhian, R., et al.. (2017). Efficient adaptive frequent pattern mining techniques for market analysis in sequential and parallel systems.. The International Arab Journal of Information Technology. 14. 175–185.
4.
Nedunchezhian, R., et al.. (2016). An Optimized Approach on Link Stability with Load Balancing in MANET using Balanced Reliable Shortest Route AOMDV (BRSR_AOMDV). Indian Journal of Science and Technology. 9(4). 2 indexed citations
5.
Nedunchezhian, R., et al.. (2016). Association Rule Mining on Big Data A Survey. International Journal of Engineering Research and. V5(5). 5 indexed citations
6.
Nedunchezhian, R., et al.. (2015). A Greedy Approach for Coverage-Based Test Suite Reduction. The International Arab Journal of Information Technology. 12. 17–23. 10 indexed citations
7.
Nedunchezhian, R., et al.. (2015). Streamlined Alarms for Intrusion Recognition System. International Journal of Intelligent Information Technologies. 11(2). 40–54. 4 indexed citations
8.
Nedunchezhian, R., et al.. (2015). Towards test suite reduction using maximal frequent data mining concept. International Journal of Computer Applications in Technology. 52(1). 48–48. 2 indexed citations
9.
Nedunchezhian, R., et al.. (2015). A Improved Incremental and Interactive Frequent Pattern Mining Techniques for Market Basket Analysis and Fraud Detection in Distributed and Parallel Systems. Indian Journal of Science and Technology. 8(18). 8 indexed citations
10.
Nedunchezhian, R., et al.. (2014). Analyzing the Point Multiplication Operation of Elliptic Curve Cryptosystem over Prime Field for Parallel Processing. The International Arab Journal of Information Technology. 11. 322–328. 6 indexed citations
11.
Nedunchezhian, R. & M. Rajalakshmi. (2014). IAPI QUAD-FILTER: AN INTERACTIVE AND ADAPTIVE PARTITIONED APPROACH FOR INCREMENTAL FREQUENT PATTERN MINING. 2 indexed citations
12.
Nedunchezhian, R., et al.. (2014). Extracting Functional Dependencies in Large Datasets Using MapReduce Model. International Journal of Intelligent Information Technologies. 10(3). 19–35. 15 indexed citations
13.
Nedunchezhian, R., et al.. (2013). Extracting Data Quality Rules Using Information Theoretic Measures. International Review on Computers and Software (IRECOS). 8(6). 1321–1327.
14.
Vivekanandan, P., M. Rajalakshmi, & R. Nedunchezhian. (2013). An Intelligent Genetic Algorithm for Mining Classification Rules in Large Datasets. Computing and Informatics / Computers and Artificial Intelligence. 32(1). 1–22. 10 indexed citations
15.
Nedunchezhian, R., et al.. (2012). Performance-Driven Load Balancing with a Primary-Backup Approach for Computational Grids with Low Communication Cost and Replication Cost. IEEE Transactions on Computers. 62(5). 990–1003. 38 indexed citations
16.
Nedunchezhian, R., et al.. (2011). Evaluation of Three Simple Imputation Methods for Enhancing Preprocessing of Data with Missing Values. International Journal of Computer Applications. 21(10). 14–19. 47 indexed citations
17.
Nedunchezhian, R., et al.. (2011). A hybrid policy for fault tolerant load balancing in grid computing environments. Journal of Network and Computer Applications. 35(1). 412–422. 48 indexed citations
18.
Nedunchezhian, R., et al.. (2011). An Empirical Selection Method for Document Clustering. International Journal of Computer Applications. 31(3). 15–19. 2 indexed citations
19.
Nedunchezhian, R., et al.. (2010). Soft Computing Applications for Database Technologies: Techniques and Issues. 5 indexed citations
20.
Nedunchezhian, R., et al.. (2006). A do-it-yourself (DIY) switched mode power conversion laboratory. 289–292. 1 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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