Prediction of Electronic parameters of Carbon Nanotube random network Field-effect Transistors under liquid gated conditions using a machine learning approach-Reference-Cited by-同舟云学术

Prediction of Electronic parameters of Carbon Nanotube random network Field-effect Transistors under liquid gated conditions using a machine learning approach

Published:2022-04-28 Issue: Volume: Page:
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Container-title:2022 IEEE International Conference on Nanoelectronics, Nanophotonics, Nanomaterials, Nanobioscience & Nanotechnology (5NANO)
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Author:

Murugathas Thanihaichelvan¹,R Veena²,Plank Natalie O.V.³,Keerththinaathan Pirunthan⁴,I Petra M.²,Mohandas Prabu⁵

Affiliation:

1. University of Jaffna,Faculty of Science,Department of Physics,Jaffna,Sri Lanka,40000

2. Universiti Brunei Darussalam,Faculty of Integrated Technologies,Brunei,BE1410

3. Victoria University of Wellington,School of Chemical and Physical Sciences,Wellington,New Zealand,6021

4. University of Jaffna,Faculty of Technology,Department of Electrical technology,Kilinochi,Sri Lanka,40000

5. National Institute of Technology Calicut,Intelligent Computing Lab,Department of Computer Science and Engineering,Kerala,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9828864/9828869/09828942.pdf?arnumber=9828942

Reference15 articles.

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5. Nonlinear prediction of chaotic time series using support vector machines. In: Neural Networks for Signal Processing [1997] VII;mukherjee;Proceedings of the 1997 IEEE Workshop,1997