A NEW HYBRID FORECASTING ALGORITHM AND ITS APPLICATION IN ECONOMIC ANALYSIS

摘要

There exists a great deal of periodic non-stationary processes in natural, social and economical phenomenon. It is very important to realize the dynamic analysis and real-time forecast within a period. In this letter, a wavelet-Kalman hybrid estimation and forecasting algorithm based on step-by-step filtering with the real-time and recursion property is put forward. It combines the advantages of Kalman filter and wavelet transform. Utilizing the information provided by multisensor effectively, this algorithm can realize not only real-time tracking and dynamic multi-step forecasting within a period, but also the dynamic forecasting between periods, and it has a great value to the system decision-making. Simulation results show that this algorithm is valuable.