Please use this identifier to cite or link to this item: http://dspace.univ-guelma.dz/jspui/handle/123456789/15030
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dc.contributor.authorOunadi, Fouad-
dc.date.accessioned2023-11-27T09:12:18Z-
dc.date.available2023-11-27T09:12:18Z-
dc.date.issued2023-
dc.identifier.urihttp://dspace.univ-guelma.dz/jspui/handle/123456789/15030-
dc.description.abstractiii ABSTRACT Cryptocurrencies have indeed experienced growing interest and popularity in recent years as digital assets independent of central banking institutions. In our re- search and development of our model, we have primarily focused our efforts on pre- dicting the price of Bitcoin, the flagship and most widely recognized cryptocurrency. We have tried several models trained on different datasets and economic and finan- cial indicators, and the best results were obtained using an MLP (Multi-Layer Percep- tron) model trained on a database containing various variations of the RSI (Relative Strength Index) economic indicator calculated over four different periods.en_US
dc.language.isofren_US
dc.publisherUniversity of Guelmaen_US
dc.subjectCryptocurrency, Bitcoin, Indicators, MLP, RSIen_US
dc.titleUn système basé sur l’apprentissage automatique pour la prédiction de la valeur des cryptomonnaiesen_US
dc.typeWorking Paperen_US
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