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Modele ARIMA w prognozowaniu sprzedaży

100%

Chrabołowska J. , Nazarko J.

tom T. 48, z. 3

791--804

W artykule przedstawiono metodykę budowy modeli ARIMA oraz ich wykorzystanie do prognozowania jednowymiarowych szeregów czasowych. Wykorzystano jedno z ogólnie stosowanych podejść zaproponowane przez Boxa i Jenkinsa. Opisano i przedyskutowano kolejne etapy tworzenia modelu na przykładzie danych dotyczących przedsiębiorstwa handlowego typu cash & carry oraz przedsiębiorstwa produkcyjnego.

The paper presents construction methodology of ARIMA models and their application in one-dimensional time series forecasting. The Box and Jenkins approach, being one of the widely used, has been employed. Consecutive phases of the model constructing have been described and discussed on the basis of a cash & carry type of trade as well as productive enterprise.

The application of the arima model in forecasting the passenger traffic on the example of border crossings between the subcarpathian province and Ukraine

100%

Dejniak D.

2018

tom Vol. 7, No. 3

155--170

Accession of Poland to the European Union meant that its eastern border became the external frontier of the Community. The next step in the European integration was joining the Schengen Zone by Poland. Polish citizens may freely travel throughout the Schengen Zone and the state was obliged to tighten its eastern border. Under these circumstances conducting research on passenger traffic has become a vital issue, with particular focus on the eastern frontier. In the article an attempt is made at examining the possibility of forecasting passenger traffic on the example of border crossing points between the Subcarpathian Province and Ukraine using the ARIMA models. Confirmation of these possibilities seems to be crucial as the number of people crossing the border is characterized by high variability and sensitivity to the political situation. The study is based on the information provided by the Polish Border Guard. The conducted time series analysis is of a multi-purpose character. It may be used to support decision making processes of investment, organizational, as well as socio-political nature.

Application of ARIMA Models for the Analysis of Utilization Process of Military Technical Objects

88%

Borucka A.

tom Vol. 37, No. 1

13--22

The newest solutions in Polish Armed Forces are implemented gradually and focus mainly on soldiers’ combat readiness. Many concurrent processes occur, for which proper analysis and interpretation could constitute command process and task realization support; however poor and standing (paper) record seems to be an obstacle in their modelling. Therefore the author of the article tried to depict the process of military technical objects exploitation based on archived data according to present methods of documents preparation, circuit and record, applicable in Polish Armed Forces. Based on that, the method of research the readiness of aircraft ships from military air base, powered by ARIMA model, was proposed. Using empirical data of two years of exploitation, the identification of researched time series, and then a few models estimation was made. Finally, the best model was chosen and verified.

Matematyczne modele prognozowania popytu na przykładzie Okręgowej Spółdzielni Mleczarskiej

75%

Dąbrowski P. , Borucka A. , Stępień B.

tom nr 5

125--149

Prognozowanie popytu jest bardzo istotnym elementem działalności każdej firmy. W artykule dokonano analizy popytu na mleko, generowanego w Okręgowej Spółdzielni Mleczarskiej w Opolu Lubelskim, celem zaproponowania wiarygodnych modeli prognostycznych. Wykorzystując opracowaną przez Boxa i Jenkinsa metodologię, opracowano model ARIMA (Autoregressive Integrated Moving Average).

Demand forecasting is a very important part of any business. In this article were the demand analyzes for milk made, generated in the District Dairy Cooperative in Opole Lubelskie, to propose reliable forecasting models. Using the Box and Jenkins methodology, was the ARIMA (Autoregressive Integrated Moving Average) model worked out.