Il volume appartiene alla collana "Studies in Fuzziness and Soft Cmputing" edito da Kacprzyk J..

The purpose of this work is to develop a neural network forecasting system based on a 2-stage approach. In the first stage, some networks are realized in order to consider different forecasting model specifications, each being referred to a particular forecasting scenario. In the second stage, the different outputs (predictions) coming from each first stage forecasting model are suitably combined to generate a final output, whose quality level is expected to be higher. Different time series are used and the corresponding results critically analyzed and compared.

A 2-stage Artificial Neural Network predictor with application to financial time series

CORAZZA, Marco
1999-01-01

Abstract

Il volume appartiene alla collana "Studies in Fuzziness and Soft Cmputing" edito da Kacprzyk J..
Soft Computing in Financial Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/10660
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