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Author: Admin | 2025-04-27
LTC dataset. Figure 6. A snippet showing a sample of the data from the BTC, ETH, and LTC datasets. (a) sample of the BTC dataset; (b) sample of the ETH dataset; (c) sample of the LTC dataset. Figure 7. Heat map representing the correlation for BTC, ETH, and LTC. Figure 7. Heat map representing the correlation for BTC, ETH, and LTC. Figure 8. The structure of a long short-term memory (LSTM) algorithm. Figure 8. The structure of a long short-term memory (LSTM) algorithm. Figure 9. The diagram of a GRU cell. Figure 9. The diagram of a GRU cell. Figure 10. The structure of a bi-directional LSTM (Bi-LSTM) algorithm. Figure 10. The structure of a bi-directional LSTM (Bi-LSTM) algorithm. Table 1. Dataset specifications. Table 1. Dataset specifications. ParameterDescriptionData TypeDateDate of the observationDateOpenDaily opening price of the selected cryptocurrencyNumberHighDaily high price of the selected cryptocurrencyNumberLowDaily low price of the selected cryptocurrencyNumberCloseDaily close price of the selected cryptocurrencyNumberClose Adj CloseDaily Adjusted close price of the selected cryptocurrencyNumber Table 2. Performance results for the proposed models. Table 2. Performance results for the proposed models. CurrencyModelRMSEMAPEBTCLSTM1031.34010.0394 Bi-LSTM1029.36170.0356 GRU1274.17060.0572ETHLSTM148.52150.2971 Bi-LSTM83.95310.1243 GRU98.31360.1479LTCLSTM9.66800.0636 Bi-LSTM8.02490.0411 GRU8.12240.0458 Table 3. Relative comparison with similar studies. Table 3. Relative comparison with similar studies. AuthorsCryptocurrenciesMethodsMAPERMSE[35]BTC - USDLSTM0.0422518.02 Bi-LSTM0.0382222.74 GRU0.0351777.31[35]ETH -USDLSTM0.064150.09 Bi-LSTM0.060147.85 GRU0.057151.62[36]BTC - USDLSTM0.0402350.53 Bi-LSTM0.0331992.88 GRU0.0533223.01[36]ETH -USDLSTM0.047183.84 Bi-LSTM0.042168.60 GRU0.047181.03[36]XRP -USDLSTM0.0630.098 Bi-LSTM0.0480.079 GRU0.0720.104Our approachBTC - USDLSTM0.0391031.340 Bi-LSTM0.0361029.362 GRU0.0571274.171Our approachETH -USDLSTM0.297148.522 Bi-LSTM0.12483.953 GRU0.14898.314Our approachLTC-USDLSTM0.0649.668 Bi-LSTM0.0418.025 GRU0.0468.122 Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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