Results found: 2

Search results

Search:
in the keywords: forecasting,

Sort By:

Limit search:

Methods of Forecasting Budget Revenues

100%

Kozicki B., Waściński T., Lisowska A.

Zeszyty Naukowe UPH seria Administracja i Zarządzanie

2020

vol. 51

issue 124

25-32

W artykule poruszony został problem z zakresu prognozowania dochodów budżetowych w Polsce po uprzednio przeprowadzonej analizie danych pierwotnych w ujęciu miesięcznym w latach 2011-1018. Dane do badań pozyskano z Głównego Urzędu Statystycznego. Badania rozpoczęto od analizy i oceny danych dotyczących dochodów budżetowych w Polsce w ujęciu dynamicznym. Następnie na podstawie uzyskanych ocen wybrano metody prognostyczne. Metody zostały poddane analizie i ocenie. Wybrano najlepszą, którą wykonano prognozowanie szeregu pierwotnego. Uzyskane rezultaty badań przedstawiono w podsumowaniu.

In the article the author raises an issue related to the forecasting of budget revenue in Poland after previous analysis primary data on a monthly basis from 2011-2018.. The research data was obtained from the Central Statistical Office. The research was initiated with the analysis and evaluation of data concerning budget revenue in Poland dynamically. Then, on the basis of the results, the prognostic methods were selected. The methods were analyzed and evaluated. The best one was selected and applied in order to conduct the forecasting of the original series. The results obtained in the research were presented in the summary.

The Use of Artifi cial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey

88%

Kitapci O., Tosun Ö., Tuna M. F., Turk T.

Journal of Marketing and Consumer Behaviour in Emerging Markets

2017

issue 1(5)

4-14

The purpose of this paper is to forecast housing prices in Ankara, Turkey using the artificial neural networks (ANN) approach. The data set was collected from one of the biggest real estate web pages during April 2013. A three-layer (input layer – one hidden layer – output layer) neural network is designed with 15 different inputs to forecast the future housing prices. The proposed model has a success rate of 78%. The results of this paper would help property investors and real estate agents in developing more effective property pricing management in Ankara. We believe that the artifi cial neural networks (ANN) proposed here will serve as a reference for countries that develop artifi cial neural networks (ANN) method-based housing price determination in future. Applying the artifi cial neural networks (ANN) approach for estimation of housing prices is relatively new in the field of housing economics. Moreover, this is the fi rst study that uses the artificial neural networks (ANN) approach for analyzing the housing market in Ankara/Turkey.

Refine search results

1 Journal of Marketing and Consumer Behaviour in Emerging Markets

1 Zeszyty Naukowe UPH seria Administracja i Zarządzanie

1 Kitapci O.

1 Kozicki B.

1 Lisowska A.

1 Tosun Ö.

1 Tuna M. F.

1 Turk T.

1 Waściński T.

1 2020

1 2017

Search results

Methods of Forecasting Budget Revenues

The Use of Artifi cial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey