
A Hybrid Regression‐Neural Network (HR‐NN) Method for Forecasting the Solar Activity
Author(s) -
Okoh D. I.,
Seemala G. K.,
Rabiu A. B.,
Uwamahoro J.,
Habarulema J. B.,
Aggarwal M.
Publication year - 2018
Publication title -
space weather
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.254
H-Index - 56
ISSN - 1542-7390
DOI - 10.1029/2018sw001907
Subject(s) - space weather , sunspot number , solar cycle 24 , artificial neural network , sunspot , meteorology , regression analysis , solar cycle , regression , index (typography) , environmental science , geomagnetic storm , earth's magnetic field , computer science , mathematics , statistics , geography , artificial intelligence , solar wind , physics , quantum mechanics , world wide web , magnetic field
The Sun is the major driver of space weather events, and as a result, most applications requiring modeling/forecasting of space weather phenomena depend largely on the activities of Sun. Accurate modeling of solar activity parameters like the sunspot number (SSN) is therefore considered significant for the quantitative modeling of space weather phenomena. Sunspot number forecasts are applied in ionospheric models like the International Reference Ionosphere model and in several other projects requiring prediction of space weather phenomena. A method called Hybrid Regression‐Neural Network that combines regression analysis and neural network learning is used for forecasting the SSN. Considering the geomagnetic Ap index during the end of the previous cycle (known as the precursor Ap index) as a reliable measurement, we predict the end of solar cycle 24 to be in March 2020 (±7 months), with monthly SSN 5.4 (±5.5). Using an estimated value of precursor Ap index as 5.6 nT for solar cycle 25, we predict the maximum SSN to be 122.1 (±18.2) in January 2025 (±6 months) and the minimum to be 6.0 (±5.5) in April 2031 (±5 months). We found from the model that on changing the assumed value of precursor Ap index (5.6 nT) by ±1 nT, the predicted peak of solar cycle 25 changes by about 11 sunspots for every 1‐nT change in the assumed precursor Ap index.