摘要：The subject of this paper is the creation and testing of an enhanced fuzzy neural network backpropagation model for the prediction of stock market indexes,including the comparison with the traditional neural network backpropagation model.The objective of the research is to gather information concerning the possibilities of using the enhanced fuzzy neural network backpropagation model for the prediction of stock market indexes focusing on transitional markets.The methodology used involves the integration of fuzzified weights into the neural network.The research results will be beneficial both for the broader investment community and the academia,in terms of the application of the enhanced model in the investment decisionmaking,as well as in improving the knowledge in this subject matter.
其他摘要：Predmet istraživanja u radu jeste kreiranje i testiranje poboljšanog fuzzy neural network backpropagation modela za predikciju berzanskih indeksa,uz poređenje sa tradicionalnim neural network backpropagation modelom.Cilj istraživanja jeste dolaženje do konkretnih saznanja o mogućnostima primene poboljšanog fuzzy neural network backpropagation modela za predikciju berzanskih indeksa,sa posebnim fokusom na tranzitorna tržišta.Metodologija korišćena u radu obuhvata integraciju fuzzyfikovanih tezina u neuro mreži.Rezultati istraživanja biće korisni kako široj investicionoj javnosti,tako i akademskoj struci,u smislu korišćenja poboljšanog modela u donošenju odluka o investiranju i unapređenju znanja u predmetnoj oblasti
