Title: Modeling of the radiation belt megnetosphere in decisional timeframes

Abstract

Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.

Inventors:

Koller, Josef; Reeves, Geoffrey D; Friedel, Reiner H.W.

Issue Date:

2013-04-23

Research Org.:

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1083288

Patent Number(s):

8428916

Application Number:

12/390,611

Assignee:

Los Alamos National Security, LLC (Los Alamos, NM)

Patent Classifications (CPCs):

G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS

G - PHYSICS G01 - MEASURING G01W - METEOROLOGY

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G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS

G06N3/0445 - {Feedback networks, e.g. hopfield nets, associative networks}

G - PHYSICS G01 - MEASURING G01W - METEOROLOGY

G01W1/10 - Devices for predicting weather conditions

G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS

G06N3/0454 - {using a combination of multiple neural nets}

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DOE Contract Number:  

AC52-06NA25396

Resource Type:

Patent

Country of Publication:

United States

Language:

English

Subject:

79 ASTRONOMY AND ASTROPHYSICS