Abstract
The neuronal network, veritable instruments of optimal solution generating and diagnosis utilized in the field of artificial intelligence, tends to increase its spectrum of applicability reaching financial-banking predictions. This paper aims to achieve a study regarding the efficiency of applying neuronal networks, with different architectures, in the process of predicting inflation rates in Romania. Also, we will compare results estimated by applying neuronal networks with results obtained through predictions gained by applying classic econometric methods.
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Stancu, S., Constantin, A.M., Predescu(Popescu), O.M. (2013). Utilizing Neuronal Calculus in Predicting Inflation. In: Fernández-Izquierdo, M.Á., Muñoz-Torres, M.J., León, R. (eds) Modeling and Simulation in Engineering, Economics, and Management. MS 2013. Lecture Notes in Business Information Processing, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38279-6_21
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DOI: https://doi.org/10.1007/978-3-642-38279-6_21
Publisher Name: Springer, Berlin, Heidelberg
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