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6 Zeszyty Naukowe. Elektryka / Politechnika Opolska

6 Kashpruk N.

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Identification of time series fuzzy models with an application to selected technological processes

Kashpruk N.

Zeszyty Naukowe. Elektryka / Politechnika Opolska

2018

z. 76

49--52

This paper presents the basic identification of time series fuzzy mod-els, based on the input-output data of time series. The main advantage of the fuzzy models is the possibility of their development on the basis of a much smaller amount of information about the system.

Applications of neuro-fuzzy system ANFIS for predictions of time series

Kashpruk N.

Zeszyty Naukowe. Elektryka / Politechnika Opolska

2017

z. 75

31--32

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.

The autocorrelation function of errors as a criterion for the selection of time series models

Kashpruk N.

Zeszyty Naukowe. Elektryka / Politechnika Opolska

2016

z. 72

29--30

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.

Identyfikacja modeli autoregresji w opisie zmian parametrów węgla

Kashpruk N.

Zeszyty Naukowe. Elektryka / Politechnika Opolska

2016

z. 74

49--54

W pracy przeprowadzono badanie identyfikacji modeli autoregresji danych dotyczących pewnego procesu technologicznego.

The analysis of time series models - analysis of the first order autoregression model

Kashpruk N.

Zeszyty Naukowe. Elektryka / Politechnika Opolska

2015

z. 71

31--32

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.

Decision making under uncertainty – basic definitions

Kashpruk N.

Zeszyty Naukowe. Elektryka / Politechnika Opolska

2014

z. 70

39-40

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.