N. Ramaraj

559 citations
28 papers · 388 · h-index 9

Impact in

  • Software top 10%
    • Metaheuristic Optimization Algorithms Research
    • Evolutionary Algorithms and Applications
    • Imbalanced Data Classification Techniques
    • Machine Learning and Data Classification

Papers in

N. Ramaraj

26 papers receiving 351 citations

Peers

N. Ramaraj
Comparison fields: 5 of 68
  • Software 29
  • Artificial Intelligence 185
  • Health Information Management 22
  • Computer Vision and Pattern Recognition 100
  • Signal Processing 40
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Shawkat Ali Australia
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Citations per field
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Citations per year

Countries citing papers authored by N. Ramaraj

Since Specialization
Citations

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

Fields of papers citing papers by N. Ramaraj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside N. Ramaraj, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with N. Ramaraj Line = papers co-authored together N. Ramaraj links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010163
2 200730
3 200730
4 201529
5 201826
6 201019
7 200712
8 20079
9 20198
10 20176
11 20076
12 20205
13 20085
14 20075
15 20085
16 20194
17 20094
18 20094
19
An Empirical Study on the Performance of Integrated Hybrid Prediction Model on the Medical Datasets
20114
20 19863

About N. Ramaraj

N. Ramaraj is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Software, having authored 28 papers that have together received 388 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (5 papers), Artificial Intelligence in Healthcare (4 papers), Software Reliability and Analysis Research (4 papers), Software Engineering Research (3 papers), Imbalanced Data Classification Techniques (3 papers), Network Security and Intrusion Detection (3 papers), Software Testing and Debugging Techniques (3 papers) and Advanced Malware Detection Techniques (2 papers). The work is most often cited by research in Software (29 citations), Artificial Intelligence (185 citations), Health Information Management (22 citations), Computer Vision and Pattern Recognition (100 citations) and Signal Processing (40 citations). N. Ramaraj has collaborated with scholars based in India, United States and Türkiye. Frequent co-authors include S. Kannan, R. Prabha, S. Baskar, C. Deisy, C. Chellappan, S.M. Kannan, S. P. Rajagopalan, Kathleen Lewis, M. Rajasekhara Babu and Ilango Paramasivam. Their work appears in journals such as Data Science Journal, EURASIP Journal on Wireless Communications and Networking, Electric Power Systems Research, Multimedia Tools and Applications and Digital Signal Processing.

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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