Estimation of the most influential science and technology factors for economic growth forecasting by soft computing technique

Economic growth may be developed on the basis on combination of different factors. In this investigation was analyzed the economic growth forecasting based on the different factors. The main goal was to analyze the influence of science and technology factors on the economic growth. Gross domestic product (GDP) was used as economic growth indicator. The method of adaptive neuro fuzzy inference system (ANFIS) was applied to the data in order to select the most influential factors for the GDP growth rate forecasting. Ten inputs are considered: research and development (R&D) expenditure in GDP, scientific and technical journal articles, patent applications for nonresidents, patent applications for residents, trademark applications for nonresidents, trademark applications for residents, total trademark applications, researchers in R&D, technicians in R&D and high-technology exports. The ANFIS process for variable selection was also implemented in order to detect the predominant factors affecting the forecasting of GDP growth rate.