Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/2193

TítuloAn evolutionary and connectionist approach for time series forecasting
Autor(es)Cortez, Paulo
Rocha, Miguel
Neves, José
Palavras-chaveTime series
Neural networks
DataAgo-1999
CitaçãoINTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSE 99), 13, Las Vegas, 1999. p. 19-24.
Resumo(s)The combination of the evolutionary and connectionist paradigms for problem solving takes a strong inspiration from living systems and is gaining an increasing attention when it comes to the development of computional systems that can handle complex and dynamic problems. One's claim is that Time Series Forecasting is a fertile domain for the test of these technologies. Therefore, a number of experiments were conducted in order to evaluate the merits or demerits of the approach, being the results compared with those obtained from the use of conventional procedures (e.g., the Holt-Winters and the ARIMA ones).
TipoconferencePaper
URIhttp://hdl.handle.net/1822/2193
Arbitragem científicayes
AcessoopenAccess
Aparece nas coleções:DSI - Engenharia da Programação e dos Sistemas Informáticos
DI/CCTC - Artigos (papers)
CAlg - Artigos em livros de atas/Papers in proceedings

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