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dc.contributor.author |
Ounadi, Fouad |
|
dc.date.accessioned |
2023-11-27T09:12:18Z |
|
dc.date.available |
2023-11-27T09:12:18Z |
|
dc.date.issued |
2023 |
|
dc.identifier.uri |
http://dspace.univ-guelma.dz/jspui/handle/123456789/15030 |
|
dc.description.abstract |
iii
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.iso |
fr |
en_US |
dc.publisher |
University of Guelma |
en_US |
dc.subject |
Cryptocurrency, Bitcoin, Indicators, MLP, RSI |
en_US |
dc.title |
Un système basé sur l’apprentissage automatique pour la prédiction de la valeur des cryptomonnaies |
en_US |
dc.type |
Working Paper |
en_US |
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