[en] AN ON-LINE LEARNING APPROACH A METHODOLOGY FOR TIME VARYING APPLICATIONS

[pt] NITZI MESQUITA ROEHL

[en] In this paper a new procedure to continuously adjust weights in a multi layered neural network is proposed. The network is initially trained by using traditional Backpropagation algorithm. After this first step, non- linear programming technique is used in order to properly on line calculate the new weights sets. This methodology is tailored to be used in time varying (non-stationary) models, eliminating necessity of retraining. Numerical results for a chaotic time series and an electricity load forecasting applications are presented.

2000-01-09

[pt] TEXTO

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INGLÊS

https://www.maxwell.vrac.puc-rio.br/colecao.php?strSecao=resultado&nrSeq=405@2