Applications of physics-informed neural networks to elucidating electron swarm transport in plasmas
Author:
Affiliation:
1. Muroran Institute of Technology,Muroran,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10625766/10625775/10626604.pdf?arnumber=10626604
Reference5 articles.
1. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
2. Deep learning for solving the Boltzmann equation of electrons in weakly ionized plasma
3. Physics-informed neural networks for solving the Boltzmann equation of the electron velocity distribution function in weakly ionized plasmas
4. Data-driven discovery of electron continuity equations in electron swarm map for determining electron transport coefficients in argon
5. Scanning drift tube measurements of electron transport parameters in different gases: argon, synthetic air, methane and deuterium
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