Volterra network modeling of the nonlinear finite-impulse reponse of the radiation belt flux

M. Taylor, I. A. Daglis, A. Anastasiadis, D. Vassiliadis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We show how a general class of spatio-temporal nonlinear impulse-response forecast networks (Volterra networks) can be constructed from a taxonomy of nonlinear autoregressive integrated moving average with exogenous inputs (NARMAX) input-output equations, and used to model the evolution of energetic particle f uxes in the Van Allen radiation belts. We present initial results for the nonlinear response of the radiation belts to conditions a month earlier. The essential features of spatio-temporal observations are recovered with the model echoing the results of state space models and linear f nite impulse-response models whereby the strongest coupling peak occurs in the preceding 1-2 days. It appears that such networks hold promise for the development of accurate and fully data-driven space weather modelling, monitoring and forecast tools.

Original languageEnglish
Title of host publicationModern Challenges in Nonlinear Plasma Physics - A Festschrift Honoring the Career of Dennis Papadopoulos
Pages221-226
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
EventModern Challenges in Nonlinear Plasma Physics - A Festschrift Honoring the Career of Dennis Papadopoulos - Halkidiki, Greece
Duration: 15 Jun 200919 Jun 2009

Publication series

NameAIP Conference Proceedings
Volume1320
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceModern Challenges in Nonlinear Plasma Physics - A Festschrift Honoring the Career of Dennis Papadopoulos
CountryGreece
CityHalkidiki
Period15/06/0919/06/09

Keywords

  • Input-output models
  • Nonlinear neural networks
  • Radiation belts

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