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| DC Field | Value | Language |
|---|---|---|
| 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 |
| Appears in Collections: | Master | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| OUNADI_FOUAD_F5.pdf | 1,29 MB | Adobe PDF | View/Open |
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