Time Series Forecasting using Recurrent Neural Networks modified by Bayesian Inference in the Learning Process

"Typically, time series forecasting is done by using models based directly on the past observations from the same sequence. In these cases, when the model is learning from data, there is not an extra quantity of noiseless data available and computational resources are unlimited. In practice, it...

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Detalles Bibliográficos
Autores Principales: Rivero C.R., Pucheta J., Otaño P., Orjuela-Cañon A.D., Patiño D., Franco L., Gorrostieta E., Puglisi J.L., Juarez G.
Formato: Objeto de conferencia (Conference Object)
Lenguaje:Inglés (English)
Publicado: Institute of Electrical and Electronics Engineers Inc. 2019
Acceso en línea:https://repository.urosario.edu.co/handle/10336/22344