@Article{GonçalvesEcheFrig:2020:SuCyPr,
               author = "Gon{\c{c}}alves, {\'{\I}}talo G. and Echer, Ezequiel and Frigo, 
                         Everton",
          affiliation = "{Universidade Federal do Pampa (UNIPAMPA)} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {Universidade Federal do Rio 
                         Grande do Sul (UFRGS)}",
                title = "Sunspot cycle prediction using Warped Gaussian process 
                         regression",
              journal = "Advances in Space Research",
                 year = "2020",
               volume = "65",
               number = "1",
                pages = "677--683",
                month = "Jan.",
             keywords = "Sunspot number, Solar cycle, Machine learning, Gaussian process.",
             abstract = "Solar cycle prediction is a key activity in space weather 
                         research. Several techniques have been employed in recent decades 
                         in order to try to forecast the next sunspot-cycle maxima and 
                         time. In this work, the Gaussian process, a machine-learning 
                         technique, is used to make a prediction for the solar cycle 25 
                         based on the annual sunspot number 2.0 data from 1700 to 2018. A 
                         variation known as Warped Gaussian process is employed in order to 
                         deal with the non-negativity constraint and asymmetrical data 
                         distribution. Tests using holdout data yielded a root mean square 
                         error of 10.0 within 5 years and 25.035.0 within 10 years. 
                         Simulations using the predictive distribution were performed to 
                         account for the uncertainty in the prediction. Cycle 25 is 
                         expected to last from 2019 to 2029, with a peak sunspot number 
                         about 117 (110 by the median) occurring most likely in 2024. Thus 
                         our method predicts that solar Cycle 25 will be weaker than 
                         previous ones, implying a continuing trend of declining solar 
                         activity as observed in the past two cycles.",
                  doi = "10.1016/j.asr.2019.11.011",
                  url = "http://dx.doi.org/10.1016/j.asr.2019.11.011",
                 issn = "0273-1177 and 1879-1948",
             language = "en",
           targetfile = "goncalves_sunspot.pdf",
        urlaccessdate = "05 maio 2024"
}