Using a set of GM(1,1) models to predict values of diagnostic symptoms
We model the time series of vibration symptoms using a set of rolling models GM(1,1). We compare proposed methods for reducing forecast error of vibration symptoms. We proposed a method for dynamic selection window length for fan mills vibration symptoms. Finally, we received a relatively (for industrial environments) small forecast error.
time series condition monitoring model selection grey system theory