Title :
System identification, modeling, and prediction for space weather environments
Author :
Vassiliadis, Dimitris
Author_Institution :
Univ. Space Res. Assoc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
fDate :
12/1/2000 12:00:00 AM
Abstract :
By now nonlinear dynamical models and neural networks have been used to predict and model a wide variety of space weather environments. This review starts with the physical basis for and a brief description of the system approach. Following that, several examples illustrate practical issues in temporal and spatiotemporal prediction and modeling. The concluding remarks discuss the future developments in this research direction
Keywords :
ionosphere; magnetosphere; solar wind; weather forecasting; forecast; forecasting; ionosphere; magnetosphere; model; modelling; neural net; neural network; nonlinear dynamical model; predict; prediction; simulation; solar wind; space weather; system identification; Circuits; Electrons; Humans; Magnetosphere; Neural networks; Predictive models; Space technology; System identification; Weather forecasting; Wind forecasting;
Journal_Title :
Plasma Science, IEEE Transactions on
