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EN
The aim of the study is to analyze the autoregressive model of the first order, describing the time series data. Construction of a process model was based on the observed variation in time of some of the measured values describing the process.
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2017
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tom z. 75
31--32
EN
This paper presents the calculations, which have been carried out on the base of the chosen technological process. The data set is a realization of a very high variation stochastic process, with constant mean value and white noise disturbances. The results of the ANFIS predictions depend on the number of data in the dataset as well as on the number of fuzzy sets in the neuro-fuzzy structure. When the dataset number and the number of fuzzy sets are increasing, then the absolute error and relative error are clearly decreasing.
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2016
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tom z. 74
49--54
PL
W pracy przeprowadzono badanie identyfikacji modeli autoregresji danych dotyczących pewnego procesu technologicznego.
EN
Everyone is faced with the necessity of daily decision-making. There are so many such situations and people take them so often that most of decisions are done unconsciously. Only the most important and most difficult decisions somehow stand out and become the subject of a specific analysis. The basic approach is always the same: going to accurate, reliable and adequate information to make the best possible choice from possible solutions.
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tom z. 72
29--30
EN
The main purpose of this paper is to review the theoretical advantages and practical methods of using the autocorrelation function of errors as a criterion for time series model selection.
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