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Van Allen Probes Bibliography is from August 2012 through September 2021
Found 3 entries in the Bibliography.
Showing entries from 1 through 3
A combined neural network- and physics-based approach for modeling plasmasphere dynamics
AbstractIn recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network-based models capture the large-scale dynamics of the plasmasphere, such as plume formation and erosion of the plasmasphere on the nightside. However, their performance depends strongly on the availability of training data. When the data coverage is limited or non-existent, as occurs during geomagnetic storms, the performance of NNs significantly de ...
Zhelavskaya, I.; Aseev, N.; Shprits, Y;
Published by: Journal of Geophysical Research: Space Physics Published on: 02/2021
YEAR: 2021   DOI: https://doi.org/10.1029/2020JA028077
plasmasphere; plasma density; neural networks; data assimilation; Kalman Filter; Machine learning; Van Allen Probes
Empirical modeling of the plasmasphere dynamics using neural networks
We propose a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural-network-based Upper hybrid Resonance Determination) algorithm for the period of October 1, 2012 - July 1, 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distributi ...
Zhelavskaya, Irina; Shprits, Yuri; c, Maria;
Published by: Journal of Geophysical Research: Space Physics Published on: 10/2017
YEAR: 2017   DOI: 10.1002/2017JA024406
inner magnetosphere; Machine learning; Models; neural networks; plasmasphere; Van Allen Probes
Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft
We present the Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm for automatic inference of the electron number density from plasma wave measurements made on board NASA\textquoterights Van Allen Probes mission. A feedforward neural network is developed to determine the upper hybrid resonance frequency, fuhr, from electric field measurements, which is then used to calculate the electron number density. In previous missions, the plasma resonance bands were manually identified, and there have been few a ...
Zhelavskaya, I.; Spasojevic, M.; Shprits, Y; Kurth, W.;
Published by: Journal of Geophysical Research: Space Physics Published on: 05/2016
YEAR: 2016   DOI: 10.1002/2015JA022132