DOI

Predicting the state of a dynamic system influenced by a chaotic immersion environment is an extremely difficult task, in which the direct use of statistical extrapolation computational schemes is infeasible. This paper considers a version of precedent forecasting in which we use the aftereffects of retrospective observation segments that are similar to the current situation as a forecast. Furthermore, we employ the presence of relatively stable correlations between the parameters of the immersion environment as a regularizing factor. We pay special attention to the choice of similarity measures or distances used to find analog windows in arrays of retrospective multidimensional observations.
Язык оригиналаанглийский
Номер статьи110
ЖурналComputation
Том9
Номер выпуска10
DOI
СостояниеОпубликовано - окт 2021

    Предметные области Scopus

  • Теоретические компьютерные науки
  • Компьютерные науки (все)
  • Моделирование и симуляция
  • Прикладная математика

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