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Okoh, D.I., Seemala, G.K., Rabiu, A.B., Uwamahoro, J., Habarulema, J.B. and Aggarwal, M. (2018) A Hybrid Regression-Neural Network (HR-NN) Method for Forecasting the Solar Activity. Space Weather, 16, 1424-1436.
https://doi.org/10.1029/2018sw001907

has been cited by the following article:

• TITLE: Prediction of the Amplitude and Main Characteristics of Solar Cycle 25

  AUTHORS: Daniel B. Berdichevsky, Rubén D. Piacentini

  KEYWORDS: Solar Corona Manifestations in the Evolution of the Solar Cycle (Sun Spots), Mathematical Techniques and Tools Used to Evaluate a Function’s Fundamental Properties, Sun Spots Since the Start of Their Recording Near Year 1774 of This Era

  JOURNAL NAME: Advances in Aerospace Science and Technology, Vol.9 No.4, December 31, 2024

  ABSTRACT: In this note, we estimate the maximum amplitude for the Solar Cycle 25. We use the curvature technique presented for earlier cycles by Verdes and coworkers. We further extrapolate the location of the solar maximum number of Sunspots, of which the prediction made is about 115 in the year 2025 and identify the arrival to the minimum in the year 2031, forecasting the main characteristics for the current Solar Cycle 25 and list a short comparison with a few other predictions.