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- W4315694839 abstract "The purpose of this study is to discover the optimal Deep Learning model for Bitcoin prediction among the Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). Our empirical results indicate that LSTM is the optimal model for predicting Bitcoin price and trend with the prediction accuracy of 88.9%. Our study serves as a stepping stone for novice cryptocurrency investors and future studies of more advanced and sophisticated algorithms. Finally, given that the ideal model for predicting the price of cryptocurrencies is still a topic of controversy, the findings of this study will serve as a valuable empirical resource for future studies." @default.
- W4315694839 created "2023-01-12" @default.
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- W4315694839 date "2022-10-27" @default.
- W4315694839 modified "2023-10-11" @default.
- W4315694839 title "Constructing a Cryptocurrency-Price Prediction Model Using Deep Learning" @default.
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- W4315694839 doi "https://doi.org/10.1109/iceet56468.2022.10007138" @default.
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