23 citations · 75 across the 10 of their papers we have counts for
5 papers · 1 filter
Prediction of Occurrence of Extreme Events using Machine Learning
J. Meiyazhagan, S. Sudharsan, A. Venkatasen +1
Machine learning models play a vital role in the prediction task in several fields of study. In this work, we utilize the ability of machine learning algorithms to predict the occu…
Constant Bias and Weak Second Periodic Forcing : Tools to Mitigate Extreme Events
S. Sudharsan, A. Venkatesan, M. Senthilvelan
We propose two potentially viable non-feedback methods, namely (i) constant bias and (ii) weak second periodic forcing as tools to mitigate extreme events. We demonstrate the effec…
Model-free prediction of emergence of extreme events in a parametrically driven nonlinear dynamical system by Deep Learning
J. Meiyazhagan, S. Sudharsan, M. Senthilvelan
We predict the emergence of extreme events in a parametrically driven nonlinear dynamical system using three Deep Learning models, namely Multi-Layer Perceptron, Convolutional Neur…
Emergence and mitigation of extreme events in a parametrically driven system with velocity-dependent potential
S. Sudharsan, A. Venkatesan, P. Muruganandam +1
In this paper, we discuss the emergence of extreme events in a parametrically driven non-polynomial mechanical system with a velocity-dependent potential. We confirm the occurrence…
Symmetrical emergence of extreme events at multiple regions in a damped and driven velocity-dependent mechanical system
Sudharsan S, Venkatesan A, Senthilvelan M
In this work, we report the emergence of extreme events in a damped and driven velocity-dependent mechanical system. We observe that the extreme events emerge at multiple points. W…