Комплексная Методика Анализа Экономических Временных Рядов Методами Нелинейной Динамики

Кумратова, Альфира Менлигуловна; Popova, E. V.; Savinskaya, D. N.; Kurnosova, N. S.

doi:10.17308/meps.2015.8/1292

meps

2015

DOI: 10.17308/meps.2015.8/1292

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Комплексная Методика Анализа Экономических Временных Рядов Методами Нелинейной Динамики

Альфира Менлигуловна Кумратова¹,

E. V. Popova²,

D. N. Savinskaya³

et al.

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2022

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The artificial intelligence method application for grain production productivity indicators predicting

Кумратова

2022

IOP Conf. Ser.: Earth Environ. Sci.

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The purpose of the article is to calculate the grain production productivity indicators prediction based on the operation mechanism of a linear cellular automatic machine. The concepts of «memory depth», «long-term memory» are given, a description of the artificial intelligence method, its approbation and interpretation of the results obtained are presented. It is shown that the grain production productivity predicting develops along cyclic trajectories; their characteristics stability is significantly higher than the stability of the periodicity of separately selected process points. The article presents a demonstration of the linear cellular automaton method operation based on the time series of grain crop yields in the Ishim district of the Tyumen region.

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The artificial intelligence method application for grain production productivity indicators predicting

Кумратова

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Комплексная Методика Анализа Экономических Временных Рядов Методами Нелинейной Динамики

Cited by 1 publication

References 0 publications

The artificial intelligence method application for grain production productivity indicators predicting

The artificial intelligence method application for grain production productivity indicators predicting

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