M. Kaliappan

1.4k total citations
23 papers, 863 citations indexed

About

M. Kaliappan is a scholar working on Computer Networks and Communications, Artificial Intelligence and Health Information Management. According to data from OpenAlex, M. Kaliappan has authored 23 papers receiving a total of 863 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 6 papers in Artificial Intelligence and 3 papers in Health Information Management. Recurrent topics in M. Kaliappan's work include Mobile Ad Hoc Networks (7 papers), Opportunistic and Delay-Tolerant Networks (5 papers) and Cognitive Radio Networks and Spectrum Sensing (4 papers). M. Kaliappan is often cited by papers focused on Mobile Ad Hoc Networks (7 papers), Opportunistic and Delay-Tolerant Networks (5 papers) and Cognitive Radio Networks and Spectrum Sensing (4 papers). M. Kaliappan collaborates with scholars based in India, Malaysia and Finland. M. Kaliappan's co-authors include S. Vimal, Mi Young Lee, S. Vimal, L. Kalaivani, C. Balasubramanian, P. Balasubramanian, Manju Khari, Nilanjan Dey, Rubén González Crespo and R. Geetha and has published in prestigious journals such as Neural Computing and Applications, Journal of Network and Computer Applications and Computer Communications.

In The Last Decade

M. Kaliappan

22 papers receiving 802 citations

Peers

M. Kaliappan

CNC

HIM

EEE

Pundru Chandra Shaker Reddy India

Abhishek Kumar India

Himansu Das India

V. Vinoth Kumar India

Piyush Kumar Pareek India

Fahad Algarni Saudi Arabia

Hanaa Salem Egypt

Abu Sarwar Zamani Saudi Arabia

Sachin Ahuja India

K. Vijayakumar India

Pundru Chandra Shaker Reddy India

M. Kaliappan

421 ×1.7

158 ×0.6

CNC

147 ×0.9

HIM

151 ×1.4

EEE

80 ×0.8

Citations per year, relative to M. Kaliappan M. Kaliappan (= 1×) peers Pundru Chandra Shaker Reddy

Countries citing papers authored by M. Kaliappan

Since Specialization

Citations

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

Fields of papers citing papers by M. Kaliappan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Kaliappan

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

All Works

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20 of 20 papers shown

Pradeepa, S., N. Sasikaladevi, S. Vimal, & M. Kaliappan. (2024). OralNet: deep learning fusion for oral cancer identification from lips and tongue images using stochastic gradient based logistic regression. Network Modeling Analysis in Health Informatics and Bioinformatics. 13(1). 7 indexed citations

Kaliappan, M., et al.. (2023). Radial Basis Function Neural Network for Intrusion Detection and Feed Forward Artificial Neural Network for Attack Mitigation in IoT. 1239–1245.

Narayanan, K. Lakshmi, R. Santhana Krishnan, Harold Robinson, et al.. (2022). Banana Plant Disease Classification Using Hybrid Convolutional Neural Network. Computational Intelligence and Neuroscience. 2022. 1–13. 79 indexed citations

Gopikumar, S., J. Rajesh Banu, Harold Robinson, et al.. (2022). Geo Spatial Based Real Time Monitoring on Eutrophic Evaluation of Porunai River Basin for Pollution Risk Assessment. European Journal of Remote Sensing. 56(1). 4 indexed citations

Vimal, S., et al.. (2021). Q Learning MDP Approach to Mitigate Jamming Attack Using Stochastic Game Theory Modelling With WQLA in Cognitive Radio Networks. 9(1). 3–14. 2 indexed citations

Ramar, K., N. Z. Jhanjhi, Sahil Verma, et al.. (2020). An attention‐based deep learning model for traffic flow prediction using spatiotemporal features towards sustainable smart city. International Journal of Communication Systems. 34(3). 86 indexed citations

Vimal, S., et al.. (2020). AI-based smart prediction of clinical disease using random forest classifier and Naive Bayes. The Journal of Supercomputing. 77(5). 5198–5219. 198 indexed citations

Vimal, S., Manju Khari, Rubén González Crespo, et al.. (2020). Energy enhancement using Multiobjective Ant colony optimization with Double Q learning algorithm for IoT based cognitive radio networks. Computer Communications. 154. 481–490. 105 indexed citations

Geetha, R., et al.. (2019). Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier. Journal of Medical Systems. 43(9). 286–286. 77 indexed citations

10.

Balasubramanian, C., et al.. (2019). Development of Big Data Predictive Analytics Model for Disease Prediction using Machine learning Technique. Journal of Medical Systems. 43(8). 272–272. 67 indexed citations

11.

Vimal, S., et al.. (2018). Optimization using Artificial Bee Colony based clustering approach for big data. Cluster Computing. 22(S5). 12169–12177. 53 indexed citations

12.

Vimal, S., L. Kalaivani, M. Kaliappan, et al.. (2018). Development of secured data transmission using machine learning-based discrete-time partially observed Markov model and energy optimization in cognitive radio networks. Neural Computing and Applications. 32(1). 151–161. 36 indexed citations

13.

Vimal, S., L. Kalaivani, & M. Kaliappan. (2017). Collaborative approach on mitigating spectrum sensing data hijack attack and dynamic spectrum allocation based on CASG modeling in wireless cognitive radio networks. Cluster Computing. 22(S5). 10491–10501. 29 indexed citations

14.

Kaliappan, M., et al.. (2016). Enhancing energy efficiency and load balancing in mobile ad hoc network using dynamic genetic algorithms. Journal of Network and Computer Applications. 73. 35–43. 25 indexed citations

15.

Balasubramanian, P., et al.. (2015). Development of a secure routing protocol using game theory model in mobile ad hoc networks. Journal of Communications and Networks. 17(1). 75–83. 30 indexed citations

16.

Kaliappan, M., et al.. (2014). Secure and Fair Cluster Head Selection Protocol for Enhancing Security in Mobile Ad Hoc Networks. The Scientific World JOURNAL. 2014. 1–6. 7 indexed citations

17.

Kaliappan, M., et al.. (2014). Enhancing secure routing in Mobile Ad Hoc Networks using a Dynamic Bayesian Signalling Game model. Computers & Electrical Engineering. 41. 301–313. 35 indexed citations

18.

Kaliappan, M., et al.. (2012). A Comprehensive Survey on Security Enhancement in Mobile Adhoc Networks using Game Theory Approaches. IEEE International Conference on Cloud Computing Technology and Science. 20(4). 18–21. 1 indexed citations

19.

Kaliappan, M., et al.. (2012). IPSec Provisioning in WiMAX Networks to Enhance the Security. 1 indexed citations

20.

Kaliappan, M., et al.. (2012). Enhancing the performance of MANET using EESCP. 225–230. 8 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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