Time Series and Its Characteristics Variability Analysis Using the Forecasting Model Based on the Basis of Interval Discrete Fuzzy Sets of the Second Type

L. Demidova, M. Stepanov
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引用次数: 1

Abstract

The approach to the problem of analyzing the variability of the time series and its characteristics in the context of developing a decision on the advisability of implementing the short-term forecasting procedure for one step forward has been considered. The Hurst exponent and fractal dimension are used as the characteristics of the time series. It is proposed to use the forecasting model on the basis of interval discrete fuzzy sets of the second type with the aim of analyzing the parameters of the generated “footprint of uncertainty” for the initial time series and the time series describing one or another of its characteristics, and deciding on the alleged success or failure of the short-term forecasting procedure for one step forward. The examples that confirm the effectiveness of the proposed approach to the problem of analyzing the variability of the time series have been given.
基于第二类区间离散模糊集预测模型的时间序列及其特征变异性分析
在就是否应向前一步实施短期预测程序作出决定的背景下,研究了分析时间序列的可变性及其特征的方法。采用Hurst指数和分形维数作为时间序列的特征。提出了基于第二类区间离散模糊集的预测模型,目的是分析初始时间序列和描述其某一特征的时间序列所产生的“不确定性足迹”的参数,并决定未来一步短期预测过程的所谓成功或失败。最后给出了分析时间序列变异性问题的实例,验证了该方法的有效性。
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