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
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.File | Dimensione | Formato | |
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1999-Belcaro_Corazza-A_2-stage Artificial_Neural_Network_predictor_with_application_to_financial_time_series-BOOK.pdf
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