S. Vennila

556 total citations
56 papers, 340 citations indexed

About

S. Vennila is a scholar working on Plant Science, General Agricultural and Biological Sciences and Insect Science. According to data from OpenAlex, S. Vennila has authored 56 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Plant Science, 12 papers in General Agricultural and Biological Sciences and 11 papers in Insect Science. Recurrent topics in S. Vennila's work include Agricultural pest management studies (19 papers), Agricultural Practices and Plant Genetics (11 papers) and Insect-Plant Interactions and Control (11 papers). S. Vennila is often cited by papers focused on Agricultural pest management studies (19 papers), Agricultural Practices and Plant Genetics (11 papers) and Insect-Plant Interactions and Control (11 papers). S. Vennila collaborates with scholars based in India and United States. S. Vennila's co-authors include Mathyam Prabhakar, O. M. Bambawale, B. Venkateswarlu, Meenu Agarwal, Satish Kumar Yadav, Y. G. Prasad, Ranjit Kumar Paul, K. Nagendran, K.A. Gopinath and Neha Chauhan and has published in prestigious journals such as PLoS ONE, Agricultural and Forest Meteorology and Computers and Electronics in Agriculture.

In The Last Decade

S. Vennila

49 papers receiving 309 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Vennila India 9 172 152 53 53 39 56 340
Farzana Nowrin Bangladesh 6 432 2.5× 84 0.6× 78 1.5× 50 0.9× 37 0.9× 7 515
P.G. Connolly New Zealand 13 259 1.5× 261 1.7× 88 1.7× 52 1.0× 30 0.8× 44 394
Andy Carmichael United States 10 85 0.5× 142 0.9× 201 3.8× 47 0.9× 31 0.8× 21 417
Francesca Salinari Italy 8 394 2.3× 46 0.3× 75 1.4× 84 1.6× 15 0.4× 18 506
Peter R. Samson Australia 10 254 1.5× 215 1.4× 20 0.4× 30 0.6× 124 3.2× 35 383
Yun Geng China 9 206 1.2× 32 0.2× 22 0.4× 208 3.9× 30 0.8× 17 402
Amrender Kumar India 9 229 1.3× 40 0.3× 33 0.6× 14 0.3× 45 1.2× 65 310
Yubin Yang United States 10 326 1.9× 70 0.5× 62 1.2× 22 0.4× 102 2.6× 22 401
Denis S. Willett United States 15 420 2.4× 266 1.8× 45 0.8× 53 1.0× 169 4.3× 37 577
José Cláudio Faria Brazil 8 125 0.7× 18 0.1× 23 0.4× 88 1.7× 86 2.2× 13 351

Countries citing papers authored by S. Vennila

Since Specialization
Citations

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

Fields of papers citing papers by S. Vennila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Vennila

This figure shows the co-authorship network connecting the top 25 collaborators of S. Vennila. A scholar is included among the top collaborators of S. Vennila 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 S. Vennila. S. Vennila 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.
Vennila, S., et al.. (2025). Renyi Entropy Predictive Data Mining And Weighted Xavier Deep Neural Classifier For Heart Disease Prediction. International Journal of Computational and Experimental Science and Engineering. 11(1). 3 indexed citations
2.
Vennila, S., et al.. (2024). Hyper-heuristic glowworm swarm optimised support vector machines for heart and thyroid disease classification. International Journal of System of Systems Engineering. 14(2). 226–246. 3 indexed citations
3.
Vennila, S., et al.. (2024). BAGGING ENSEMBLE MINING TECHNIQUE WITH DEEP BELIEF NETWORK (DBN) ALGORITHM-BASED HEART DISEASE PREDICTION. ICTACT Journal on Image and Video Processing. 14(4). 3293–3300. 2 indexed citations
4.
5.
Vennila, S., et al.. (2023). Bidirectional Recurrent Network and Neuro-fuzzy Frequent Pattern Mining for Heart Disease Prediction. SN Computer Science. 4(4). 1 indexed citations
6.
Vennila, S., et al.. (2022). Impact of climate change on Helicoverpa armigera voltinism in different Agro-Climatic Zones of India. Journal of Thermal Biology. 106. 103229–103229. 4 indexed citations
7.
Prabhakar, M., et al.. (2021). Evaluation of linear and nonlinear models for temperature driven development of Spodoptera litura (Fabricius) on soybean crop. Journal of Agrometeorology. 23(2). 169–175. 2 indexed citations
8.
Singh, Sushil Kumar, et al.. (2021). Forecasting Helicoverpa armigera (Lepidoptera: Noctuidae) larval phenology in pigeonpea and chickpea crops using growing degree days. Journal of Agrometeorology. 22(3). 320–331. 2 indexed citations
9.
Vennila, S., et al.. (2020). A Proficient Optimized Feature Selection Method Germane For Autism Spectrum Disorder Classification. International journal of scientific and technology research. 9(2). 1133–1137.
10.
Vennila, S., et al.. (2019). Diversity analysis reveals genetic homogeneity among Indian populations of legume pod borer, Maruca vitrata (F.). 3 Biotech. 9(9). 319–319. 8 indexed citations
11.
Paul, Ranjit Kumar, et al.. (2019). Prediction of early blight severity in tomato (Solanum lycopersicum) by machine learning technique. The Indian Journal of Agricultural Sciences. 89(11). 1921–1927. 7 indexed citations
12.
Kumar, Amrender, et al.. (2018). Possible future climate for rice growing regions in India: Visualising 2050 and pest-related impact thereof. The Indian Journal of Agricultural Sciences. 88(2). 197–211. 2 indexed citations
13.
Vennila, S., et al.. (2017). Artificial neural network techniques for predicting severity of Spodoptera litura(Fabricius) on groundnut. Journal of Environmental Biology. 38(3). 449–456. 7 indexed citations
14.
Jha, Girish Kumar, et al.. (2016). Predicting the severity of Spodoptera litura on groundnut in relation to climatic variability using ordinal logistic model. Journal of Agrometeorology. 18(2). 282–287. 1 indexed citations
15.
Kumar, Amrender, et al.. (2015). Non-parametric analysis of long-term rainfall and temperature trends in India.. 69(2). 135–147. 4 indexed citations
16.
Vennila, S., et al.. (2015). Disease scenario of tomato in mid-hills and sub-tropical plains of India. Indian journal of plant protection. 43(2). 264–265. 1 indexed citations
17.
Vennila, S., et al.. (2014). Ornamental hosts of cotton mealybug (Phenacoccus solenopsis). The Indian Journal of Agricultural Sciences. 84(1). 3 indexed citations
18.
Vennila, S., et al.. (2011). Approaches to weather based prediction of insects: a case study on cotton pink bollworm Pectinophora gossypiella. Indian journal of plant protection. 39(3). 163–169. 1 indexed citations
19.
Vennila, S., et al.. (2010). Biology of the Mealybug,Phenacoccus solenopsison Cotton in the Laboratory. Journal of Insect Science. 10(115). 1–9. 56 indexed citations
20.
Vennila, S. & D. Rajagopal. (2003). Phenology of tropical carabids (Coleoptera: Carabidae). Journal of Entomological Research. 27(1). 1–7. 2 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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