In recent years, artificial intelligence (AI) techniques have been developed rapidly. With the
help of big data, massive parallel computing, and optimization algorithms, machine learning …

Plasma parameter inversion is important for space plasma physics and applications,
particularly for inhomogeneous magnetized plasmas. A physics-informed deep neural …

Electromagnetic (EM) wave propagation and inversion in complex time-varying medium is a
challenging problem, particularly for plasma applications. We extend the EM wave–plasma …

We report observations of stimulated electromagnetic emission (SEE) induced by high
power high frequency (HF) radio waves near the third electron gyroharmonic (3) at …

In a multi-terminal modular multilevel converter-based high voltage direct current (MMC-
HVDC) grid, due to the coupling between converter stations, it is difficult to obtain an …

In this work, exploitation of artificial intelligence algorithms for the design of forward-wave
amplifier is proposed and discussed. The multilayer perceptron (MLP), a quintessential …

In a complex electromagnetic environment, numerical solution of partial differential
equations (PDEs) and how to sample less data to invert spatio-temporal dynamics to …

Electron scattering cross sections have been acquired both theoretically and experimentally
over the last few decades. By combining scattering data with machine learning, this work is …

In this letter, we introduce a backpropagation (BP) neural network-based inversion method
for deriving the equivalent electromagnetic parameters of cellular microwave absorbing …

The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma
sheath. Due to the influence of the inhomogeneous flow field around the vehicle …