K. S. Kumar

发表

Diverse dynamical characteristics across the frequency spectrum of wind speed fluctuations

G. V. Drisya, K. Satheesh Kumar, K. Asokan, 2018 .

Deterministic prediction of surface wind speed variations 1421

G. V. Drisya, D. C. Kiplangat, K. Asokan, 2014 .

Deterministic nature of the underlying dynamics of surface wind fluctuations

K. Satheesh Kumar, K. Asokan, K. S. Kumar, 2012 .

Day-ahead prediction using time series partitioning with Auto-Regressive model

G. V. Drisya, D. C. Kiplangat, K. S. Kumar, 2022, 2203.14910.

Symbolic regression-based improved method for wind speed extrapolation from lower to higher altitudes for wind energy applications

Drisya Alex Thumba, K. Asokan, K. S. Kumar, 2020 .

Recurrence Network-Based Approach to Distinguish Between Chaotic and Quasiperiodic Solution

Drisya Alex Thumba, K. S. Kumar, Ardhana Mohan, 2019 .

Universal consequences of the presence of excluded volume interactions in dilute polymer solutions undergoing shear flow.

K. S. Kumar, J. R. Prakash, 2004, The Journal of chemical physics.

A Novel Approach for the Extrapolation of Wind Speed Time Series to Higher Altitude Using Machine Learning Model

G. V. Drisya, K. S. Kumar, P. Valsaraj, 2018, 2018 International CET Conference on Control, Communication, and Computing (IC4).

A Wavelet, AR and SVM based hybrid method for short-term wind speed prediction

G. V. Drisya, K. S. Kumar, 2022, ArXiv.

Analysis of the fluctuations of the total electron content (TEC) measured at Goose Bay using tools of nonlinear methods

K. S. Kumar, C. Venugopal, G. Renuka, 2004 .

Empirical Estimation of Return Period and Distribution of Duration of Wind Speed Exceedances

G. V. Drisya, D. C. Kiplangat, K. Asokan, 2018, 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS).

Chaotic dynamics of periodically forced spheroids in simple shear flow with potential application to particle separation

K. S. Kumar, T. Ramamohan, C. V. A. Kumar, 1995 .

Review of chaos in the dynamics and rheology of suspensions of orientable particles in simple shear flow subject to an external periodic force

K. Satheesh Kumar, K. Radhakrishnan, C. V. Anil Kumar, 2005 .

Deterministic prediction of surface wind speed variations

G. V. Drisya, K. Satheesh Kumar, K. Asokan, 2014 .

Universal consequences of the presence of excluded volume interactions in dilute polymer solutions undergoing shear flow.

K. S. Kumar, J. R. Prakash, 2004, The Journal of chemical physics.

Equilibrium swelling and universal ratios in dilute polymer solutions: Exact Brownian dynamics simulations for a delta function excluded volume potential

K. S. Kumar, J. R. Prakash, 2002, cond-mat/0211680.

From conventional governance to e-democracy: Tracing the evolution of e-governance research trends using network analysis tools

C. Prem Sankar, K. Satheesh Kumar, N. Bindu, 2019, Gov. Inf. Q..

Research collaboration and knowledge sharing in e-governance

K. S. Kumar, N. Bindu, C. Sankar, 2019, Transforming Government: People, Process and Policy.

Dynamics of Semantic Networks of Independence Day Speeches

K. Satheesh Kumar, C Prem Sankar, S S Vinod Chandra, 2018, 2018 International CET Conference on Control, Communication, and Computing (IC4).

Learning from Bees: An Approach for Influence Maximization on Viral Campaigns

C Prem Sankar, Asharaf S, K Satheesh Kumar, 2016, PloS one.

Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach

K. Satheesh Kumar, Meenu R. Mridula, Ashalatha S. Nair, 2018, PLoS Comput. Biol..

A broad overview of interactive digital marketing: A bibliometric network analysis

Yogesh Kumar Dwivedi, Yogesh K. Dwivedi, K. Satheesh Kumar, 2021, Journal of Business Research.

Agent-based multi-edge network simulation model for knowledge diffusion through board interlocks

C. Prem Sankar, Drisya Alex Thumba, T. R. Ramamohan, 2020, Expert Syst. Appl..

Exploratory social network analysis of affiliation networks of Indian listed companies

C. Prem Sankar, K. Satheesh Kumar, K. Asokan, 2015, Soc. Networks.

Improved week-ahead predictions of wind speed using simple linear models with wavelet decomposition

K. Satheesh Kumar, K. Asokan, Dennis Cheruiyot Kiplangat, 2016 .

Improved tests for non-linearity using network-based statistics and surrogate data

M C Mallika, K Asokan, K S Anil Kumar, 2021, Pramana.

Comparison of Variations of TEC at Disturbed and Quiet Time Using Nonlinear Dynamics Tools

K. Asokan, K. S. Kumar, T. Ramamohan, 2018, Journal of Geophysical Research: Space Physics.

Nonlinear time series analysis of the fluctuations of the geomagnetic horizontal field

K. S. Kumar, C. Venugopal, G. Renuka, 2002 .

Empirical mode decomposition and chaos based prediction model for wind speed oscillations

G. V. Drisya, K. Satheesh Kumar, K. S. Kumar, 2015, 2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS).

Time series analysis of duty cycle induced randomness in thermal lens system

K. S. Kumar, M. S. Swapna, V. Raj, 2020, Optik.

Trust Based Stock Recommendation System – A Social Network Analysis Approach☆

C. Prem Sankar, K. Satheesh Kumar, R. Vidyaraj, 2015 .

Wind speed forecast using random forest learning method

G. V. Drisya, K. Asokan, K. S. Kumar, 2022, ArXiv.

Cross-location wind speed forecasting for wind energy applications using machine learning based models.

Valsaraj Perumpalot, G. V. Drisya, K. Satheesh Kumar, 2018, 1808.03480.

Modelling the Wind Speed Oscillation Dynamics

K. Asokan, K. S. Kumar, 2012 .