COMPARATIVE ANALYSIS OF BUILDING PRODUCTION FORECASTING USING REGRESSION, NEURAL NETWORKS AND ARIMA METHODS
Journal Title: Scientific Journal of the Military University of Land Forces - Year 2010, Vol 157, Issue 3
Abstract
The study analyzed the possibility of forecasting of Lower Silesia building production using regression, neural networks and ARIMA methods. For the forecasting regression method, daily weather data of Lower Silesia were used. Potential predictors were eliminated by checking the following: the normality of their distributions (Kolmogorov-Smirnov , Lilliefoes and Chi square tests), the condition of absence of correlation between variables (correlation coefficient) and the condition of equality of variance between the variables (Levene, Brown-Forsythe tests). To perform calculations with the neural networks method, MLP and RBF networks were used by entering all the weather data obtained. In the case of the ARIMA method, forecasting was carried out on the basis of statistical values from previous years. An analysis of errors was performed by calculating ME, MAE, MPE and MAPE errors. The direction of further research was proposed.
Authors and Affiliations
Magdalena ROGALSKA , Zdzisław HEJDUCKI
Keywords
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