Prasannavenkatesan Theerthagiri

According to our database, Prasannavenkatesan Theerthagiri authored at least 21 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2024

Deep SqueezeNet learning model for diagnosis and prediction of maize leaf diseases.

Prasannavenkatesan Theerthagiri, A. Usha Ruby, J. George Chellin Chandran, Tanvir Habib Sardar, Ahamed Shafeeq B. M.

J. Big Data, December, 2024

RG-SVM: Recursive gaussian support vector machine based feature selection algorithm for liver disease classification.

Prasannavenkatesan Theerthagiri, Devarayapattana Siddalingaiah Sahana

Multim. Tools Appl., June, 2024

Prediction and classification of minerals using deep residual neural network.

Prasannavenkatesan Theerthagiri, A. Usha Ruby, J. George Chellin Chandran

Neural Comput. Appl., February, 2024

D-Resnet: deep residual neural network for exploration, identification, and classification of beach sand minerals.

Prasannavenkatesan Theerthagiri, A. Usha Ruby, B. N. Chaithanya, Renuka R. Patil, Swasthika Jain

Multim. Tools Appl., February, 2024

2023

CoFEE: Context-aware futuristic energy estimation model for sensor nodes using Markov model and autoregression.

Prasannavenkatesan Theerthagiri

Int. J. Commun. Syst., August, 2023

Seasonal learning based ARIMA algorithm for prediction of Brent oil Price trends.

Prasannavenkatesan Theerthagiri, A. Usha Ruby

Multim. Tools Appl., July, 2023

Stress emotion recognition with discrepancy reduction using transfer learning.

Prasannavenkatesan Theerthagiri

Multim. Tools Appl., February, 2023

Diagnosis and Classification of the Diabetes Using Machine Learning Algorithms.

Prasannavenkatesan Theerthagiri, A. Usha Ruby, Vidya J

SN Comput. Sci., 2023

2022

Mobility prediction for random walk mobility model using ARIMA in mobile ad hoc networks.

Prasannavenkatesan Theerthagiri

J. Supercomput., 2022

Predictive analysis of cardiovascular disease using gradient boosting based learning and recursive feature elimination technique.

Prasannavenkatesan Theerthagiri

Intell. Syst. Appl., 2022

k-means clustering based energy and trust management routing algorithm for mobile ad-hoc networks.

C. Gopala Krishnan, Nishan A. H., Prasannavenkatesan Theerthagiri

Int. J. Commun. Syst., 2022

Cardiovascular disease prediction using recursive feature elimination and gradient boosting classification techniques.

Prasannavenkatesan Theerthagiri, Jyothiprakash Vidya

Expert Syst. J. Knowl. Eng., 2022

RFFS: Recursive random forest feature selection based ensemble algorithm for chronic kidney disease prediction.

Prasannavenkatesan Theerthagiri, A. Usha Ruby

Expert Syst. J. Knowl. Eng., 2022

Mobility speed prediction using ARIMA and RNN for random walk mobility model in mobile ad hoc networks.

Prasannavenkatesan Theerthagiri, Menakadevi Thangavelu

Concurr. Comput. Pract. Exp., 2022

Vehicular multihop intelligent transportation framework for effective communication in vehicular ad-hoc networks.

Prasannavenkatesan Theerthagiri, Chandrasekaran Gopala Krishnan

Concurr. Comput. Pract. Exp., 2022

2021

Prognostic Analysis of Hyponatremia for Diseased Patients Using Multilayer Perceptron Classification Technique.

Prasannavenkatesan Theerthagiri, C. Gopala Krishnan, Nishan A. H.

EAI Endorsed Trans. Pervasive Health Technol., 2021

Probable Forecasting of Epidemic COVID-19 in Using COCUDE Model.

Prasannavenkatesan Theerthagiri

EAI Endorsed Trans. Pervasive Health Technol., 2021

Cardiovascular Disease Prediction using Recursive Feature Elimination and Gradient Boosting Classification Techniques.

Prasannavenkatesan Theerthagiri, Vidya J

CoRR, 2021

Forecasting hyponatremia in hospitalized patients using multilayer perceptron and multivariate linear regression techniques.

Prasannavenkatesan Theerthagiri

Concurr. Comput. Pract. Exp., 2021

2020

FUCEM: futuristic cooperation evaluation model using Markov process for evaluating node reliability and link stability in mobile ad hoc network.

Prasannavenkatesan Theerthagiri

Wirel. Networks, 2020

2019

Futuristic speed prediction using auto-regression and neural networks for mobile ad hoc networks.

Prasannavenkatesan Theerthagiri, Menakadevi Thangavelu

Int. J. Commun. Syst., 2019