基于小波函数与改进时间序列的数字经济成熟度研究  

Research on Maturity of Digital Economy Based on Wavelet Function and Improved Time Series

作　　者：陈彬 徐欢 周珑 CHEN Bin;XU Huan;ZHOU Long(China Southern Power Grid Co.,Ltd.,Guangzhou 510000;China Southern Grid Digital Grid Research Institute Co.,Ltd.,Guangzhou 510000)

机构地区：[1]中国南方电网责任有限公司,广州510000 [2]南方电网数字电网研究院有限公司,广州510000

出　　处：《计算机与数字工程》2023年第12期2807-2813,共7页Computer & Digital Engineering

摘　　要：针对时间序列算法右侧数据畸变严重,全局搜索能力弱的问题,提出基于小波函数的改进时间序列算法(ITSWF)。首先采用小波函数对右侧畸变数据进行分包,使数据呈现片段式有序,减少不同时间的数据畸变性,削弱时间、维度对计算结果的影响。然后,小波函数将数据分包,形成不同维度的子时间序列,并对不同维度子时间序列进行协同进化和最优位置共享。经过仿真测试,ITSWF算法的计算精度和收敛速度均优于CTS、ITS算法。最后,通过设置初始值和阈值构建ITSWF模型,对数字经济经济成熟度进行预测,且结果显示,ITSWF模型在数字经济成熟度分析方面,其准确率有所改进。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.

关 键 词：小波函数 时间序列 数字经济 成熟度预测 

分 类 号：O141.4[理学—数学]