Parametric identification of solar series based on an adaptive parallel methodology

In this work we present an adaptive parallel methodology to optimize the identification of time series through parametric models, applying it to the case of sunspot series. We employ high precision computation of system identification algorithms, and use recursive least squares processing and ARMAX (Autoregressive Moving Average Extensive) parametric modelling. This methodology could be very useful when the high precision mathematical modelling of dynamic complex systems is required. After explaining the proposed heuristics and the tuning of its parameters, we show the results we have found for several solar series using different implementations. Thus, we demonstrate how the result precision improves.