Prediction of economic growth by extreme learning approach based on science and technology transfer
作者： Petra Karanikić , Igor Mladenović , Svetlana Sokolov-Mladenović , Meysam Alizamir
DOI: 10.1007/S11135-016-0337-Y
关键词:
摘要: The purpose of this research is to develop and apply the extreme learning machine (ELM) forecast gross domestic product (GDP) growth rate. Economic may be developed on basis combination different factors. In investigation was analyzed economic prediction based science technology transfer. main goal analyze influence number granted European patents by field technology. GDP used as indicator. ELM results are compared with genetic programming (GP) artificial neural network (ANN). reliability computational models were accessed simulation using several statistical indicators. Coefficient determination for method 0.9841, ANN it 0.7956 GP 0.7561. Based upon results, demonstrated that can utilized effectively in applications forecasting.
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