Study of Geomagnetic Storms During Ascending Phase of Solar Cycle 25 and it's Bio- inspired Prediction

The geomagnetic storms have been classified based on the Dst index. The investigation of the ascending phase of Solar Cycle 25 has revealed that 69 moderate storms, 3 intense storms, and one severe storm had occurred from 2019 to 2023 till June. In the present work, we have correlated the coronal mass ejection (CMEs) and geomagnetic storms with a phase of solar cycle 25. In this research work it has also been tried to forecast the disturbed storm time index with artificial neural network (ANN) and bio inspired algorithm called as particle swarm optimization (PSO) along it with genetic algorithm (GA). The parameters such as solar wind density, plasma speed, and magnetic field of solar wind have been applied to analyze geomagnetic storms. In this research work It has also been correlated the rate of occurrence of geomagnetic storms with solar activity. Along with this correlative result, we have also found that the bio-inspired hybridized computational techniques as ANN+ PSO and ANN+PSO+GA have shown very much accurate results for various duration of Dst index.

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Publication Details

Journal
Prabha Materials Science Letters
Published
2025-03-01
DOI
https://doi.org/10.33889/pmsl.2025.4.2.014
Citations
1
Primary Topic
Solar and Space Plasma Dynamics
Type
article
Field-Weighted Citation Impact
1.15
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article

Study of Geomagnetic Storms During Ascending Phase of Solar Cycle 25 and it's Bio- inspired Prediction

Kalpana Patel, R. P. Patel, M. Mohan
1 citations
Prabha Materials Science Letters
Solar and Space Plasma Dynamics
1.15
article

Study of Geomagnetic Storms During Ascending Phase of Solar Cycle 25 and it's Bio- inspired Prediction

Kalpana Patel, R. P. Patel, M. Mohan
article en
1 citations

Abstract

The geomagnetic storms have been classified based on the Dst index. The investigation of the ascending phase of Solar Cycle 25 has revealed that 69 moderate storms, 3 intense storms, and one severe storm had occurred from 2019 to 2023 till June. In the present work, we have correlated the coronal mass ejection (CMEs) and geomagnetic storms with a phase of solar cycle 25. In this research work it has also been tried to forecast the disturbed storm time index with artificial neural network (ANN) and bio inspired algorithm called as particle swarm optimization (PSO) along it with genetic algorithm (GA). The parameters such as solar wind density, plasma speed, and magnetic field of solar wind have been applied to analyze geomagnetic storms. In this research work It has also been correlated the rate of occurrence of geomagnetic storms with solar activity. Along with this correlative result, we have also found that the bio-inspired hybridized computational techniques as ANN+ PSO and ANN+PSO+GA have shown very much accurate results for various duration of Dst index.

Prabha Materials Science LettersVol. 4(2)
SRM Institute of Science and Technology (IN), Institute of Management Technology (IN), Mody University of Science and Technology (IN)
Openalex Percentile: Top 21%
Solar and Space Plasma Dynamics
1.15
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