Prediction of future evolution of solar cycle 24 using machine learning techniques
Abstract
Forecasting the solar activity is of great importance not only for its effect on the climate of the Earth but also on the telecommunications, power lines, space missions and satellite safety. In the present work, machine learning using Artificial Neural Networks (ANNs) called Nonlinear Autoregressive Network (NAR) with Exogenous Inputs (NARX) have been applied for the prediction of future evolution of the present sunspot cycle. NARX network is able to combine the performance of ANN algorithm with nonlinear autoregressive method to handle problems such as finding dependencies among solar indices and prediction of solar cycle evolution.
- Publication:
-
Long-term Datasets for the Understanding of Solar and Stellar Magnetic Cycles
- Pub Date:
- February 2018
- DOI:
- 10.1017/S1743921318001485
- Bibcode:
- 2018IAUS..340..317G
- Keywords:
-
- Solar cycle;
- Machine learning