Zobrazeno 1 - 10
of 230
pro vyhledávání: '"Meiyazhagan A"'
Autor:
Shohei Nishimura, Neel Narayan, Onur Sahin, Ashleigh D. Smith McWilliams, Kristen A. Miller, Devashish Salpekar, Zixing Wang, Jarin Joyner, Angel A. Martí, Robert Vajtai, Meiyazhagan Ashokkumar, Pulickel M. Ajayan
Publikováno v:
Carbon Trends, Vol 4, Iss , Pp 100059- (2021)
The leather industry generates approximately ten million tons of solid bio-wastes that can be used to synthesize various multifunctional materials with exciting properties. One such approach involves developing advanced hybrid materials, which is con
Externí odkaz:
https://doaj.org/article/ea713613ccad4061a096bf70f1e4a72b
Publikováno v:
Catalysts, Vol 8, Iss 12, p 601 (2018)
The energy crisis is one of the most serious issue that we confront today. Among different strategies to gain access to reliable fuel, the production of hydrogen fuel through the water-splitting reaction has emerged as the most viable alternative. Sp
Externí odkaz:
https://doaj.org/article/77ae86dd44af42d799f5cf47ec19c9fa
We investigate the physics informed neural network method, a deep learning approach, to approximate soliton solution of the nonlinear Schr\"odinger equation with parity time symmetric potentials. We consider three different parity time symmetric pote
Externí odkaz:
http://arxiv.org/abs/2204.08596
Autor:
Meiyazhagan, J., Senthilvelan, M.
We forecast two different chaotic dynamics of the quasiperiodically forced logistic map using the well-known deep learning framework Long Short-Term Memory. We generate two data sets and use one in the training process and the other in the testing pr
Externí odkaz:
http://arxiv.org/abs/2203.11151
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 occurrence of extreme events in a nonlinear mechanical system. Extreme eve
Externí odkaz:
http://arxiv.org/abs/2110.09304
We predict the emergence of extreme events in a parametrically driven nonlinear dynamical system using three Deep Learning models, namely Multi-Layer Perceptron, Convolutional Neural Network and Long Short-Term Memory. The Deep Learning models are tr
Externí odkaz:
http://arxiv.org/abs/2107.08819
Publikováno v:
In Materials Chemistry and Physics 1 May 2024 318
Autor:
Fernando, Niranjala, Kannan, Harikishan, Robles Hernandez, Francisco C., Ajayan, Pulickel M., Meiyazhagan, Ashokkumar, Abdelkader, Amr M.
Publikováno v:
In Journal of Energy Storage 1 November 2023 71
Autor:
Meiyazhagan, S., Kavitha, E.R., Yugeswaran, S., Santhanamoorthi, N., Jiang, Guangming, Suresh, K.
Publikováno v:
In Journal of Water Process Engineering October 2023 55
Autor:
Jaganathan, Meiyazhagan, Bakthavatchalam, Tamil Arasan, Vadivel, Murugesan, Murugan, Selvakumar, Balu, Gopinath, Sankarasubbu, Malaikannan, Ramaswamy, Radha, Sethuraman, Vijayalakshmi, Malomed, Boris A.
Publikováno v:
In Chaos, Solitons and Fractals: the interdisciplinary journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena July 2023 172