Research on Maturity of Digital Economy Based on Wavelet Function and Improved Time Series
CHEN Bin
XU Huan
ZHOU Long
Abstract：Aiming at the serious data distortion and weak global search ability of time series algorithm,an improved time se-ries algorithm based on wavelet function(ITSWF)is proposed.Firstly,the wavelet function is used to subcontract the right distorted data,so that the data is in fragment order,reduce the data distortion at different times,and weaken the influence of time and dimen-sion on the calculation results.Then,the wavelet function subcontracts the data to form sub time series with different dimensions,and co evolution and optimal location sharing are carried out for sub time series with different dimensions.The simulation results show that the calculation accuracy and convergence speed of ITSWF algorithm are better than CTS and ITS algorithms.Finally,the ITSWF model is constructed by setting the initial value and threshold to predict the economic maturity of digital economy,and the results show that the accuracy of ITSWF model is improved in the analysis of digital economic maturity.
Keywords：wavelet functiontime seriesdigital economymaturity prediction
Publication Date：2023-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 2807-2813 )