Optimization Approach to Space Weather Prediction

Semeniv, O. V.; Sidorenko, V. I.; Shatokhina, Yuliya V.; Cheremnykh, O. K.; Yatsenko, Vitaliy A.

doi:10.1615/jautomatinfscien.v40.i8.50

Cited by 3 publications

(6 citation statements)

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“…On Fig. 3 the results of Dst-index behaviour modeling using models (18) and (19) are shown together with observations. The time scaled window of 150 hours was chosen for the analysis of u(k) behaviour and determination of maximal changes of the u(k) and δ calculation.…”

Section: Resultsmentioning

confidence: 90%

“…and the second one was identified using linear and nonlinear nodes β = 0 The structure and parameters of models (18) and (19) were numerically determined using the identification algorithm and training data set of measurements for N = 2000 hours. The statistical characteristics of these models are the linear correlation coefficient (LC) and the residual mean square (RMS): model ( 18) LC = 0.96, RMS = 3.36; model ( 19) LC = 0.97, RMS = 3.19.…”

Section: Resultsmentioning

confidence: 99%

“…4 the results of Dst-index prediction interval estimation with models ( 18) and ( 19) are shown. nonlinear model (19).…”

Section: Resultsmentioning

confidence: 99%

“…In the paper, according to [2,[15][16][17][18][19][20], the polynomial model for predicting Dst-index has been used. It is known that Burton (BMR) linear equation [21] describes Dst-index dynamics…”

Section: Introductionmentioning

confidence: 99%

“…As a result the problem of Dst-index prediction, can be reduced to the model (4) identification. In previous studies [19,20,24] an original algorithm of model structure and parameters identification has been developed.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

The combined approach for space weather prediction with a guaranteed method and evolutionary algorithm

Semeniv¹

2015

J. Phys. Stud.

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The problem of space weather prediction using guaranteed approach and solar wind parameters is considered. The original approach for space weather prediction based on a discrete dynamic model, evolutionary algorithm and a guaranteed interval estimation method is proposed. The problem of discrete model identification is formulated as a nonlinear programming problem with constraints. A new algorithm of Dst-index prediction using guaranteed interval estimation method is described. The model for the prediction of geomagnetic storms was constructed and the interaction between the solar wind parameters and the magnetosphere was discussed. The dependence between prediction accuracy and the forecasting horizon is analyzed.

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Section: Resultsmentioning

confidence: 90%

Section: Resultsmentioning

confidence: 99%

“…4 the results of Dst-index prediction interval estimation with models ( 18) and ( 19) are shown. nonlinear model (19).…”

Section: Resultsmentioning

confidence: 99%