The cold regions’ temperature nonlinear prediction method basing on phase space reconstruction and Volterra filter

Abstract

The chaos characteristics of temperature time series in cold regions’ winter were studied. Firstly, it is determined by 0-1 time series of chaotic test method that the chaos characteristics of temperature in cold regions’ winter. Secondly, reconstructing phase spaces, and using the C-C algorithm and G-P algorithm to determine the delay time and embedding dimension. Then, based on phase space reconstruction and Vinterra filter, a temperature prediction method in cold regions’ winter is proposed. Case analysis shows that the proposed method is superior to the common model in accuracy, prediction error and effect, and the prediction method is feasible and effective.