期刊名称：Eastern-European Journal of Enterprise Technologies
印刷版ISSN：1729-3774
电子版ISSN：1729-4061
出版年度：2018
卷号：1
期号：4
页码：32-42
DOI：10.15587/1729-4061.2018.121620
语种：English
出版社：PC Technology Center
摘要：Adaptive combined models of hybrid and selective types for prediction of time series on the basis of a program set of adaptive polynomial models of various orders were offered. Selection in these models is carried out according to B-, R-, P-criteria with automatic formation of the basic set of models based on the adaptive D-criterion. It was found that these models had the maximum accuracy in the case of short-term and medium-term prediction of time series.Adaptive combined selective prediction models based on the R- and B-criteria of selection with identification of similarities in the retrospection of time series by the nearest neighbor method was proposed. An adaptive combined hybrid model of prediction with identification of similarities in the retrospection of time series was constructed. It was found that these models had the highest accuracy in the case of medium-term prediction of time series.Estimation of the prediction efficiency of various combined models depending on the level of persistency of time series was made. It has been found that in the case of short-term prediction for the prediction period τ≤2, the adaptive combined hybrid prediction model is the most accurate. Selective models with various selection criteria are effective in predicting persistent time series with the Hurst index H>0.75 for the prediction period τ>2. In the case of prediction of time series with the Hurst index for the prediction period τ>2, the adaptive combined hybrid and selective models with identification of similarities in the retrospection of the time series are more precise.
关键词：prediction of time series;search for similarities;adaptive combined model;Hurst index
