Time series forecasting based on a multidimensional Taylor network model with clustering of dynamic characteristics

Abstract

In view of the difficulty of modelling time-varying nonlinear systems, a multidimensional Taylor network (MTN) model based on dynamic characteristic clustering is proposed to establish an online time series forecasting model. The construction method of a MTN, the definitions of the dynamic characteristics, and their similarity criteria are discussed. Specific steps of the MTN online model, based on dynamic clustering, are given. A practical example is presented to demonstrate how the proposed method works in a real application, and its effectiveness is verified.