This study proposes three types of Recurrent Neural Networks (RNNs): namely, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bi-Directional LSTM ...

This article evaluates different architectures for prediction based on statistical approaches, machine learning (ML), and deep learning (DL) techniques.

18 февр. 2023 г. · This study proposes three types of Recurrent Neural Networks (RNNs): namely, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bi-Directional LSTM ...

The paper suggests that the prediction models presented in it are accurate in predicting cryptocurrency prices and can be beneficial for investors and traders.

Results reveal that deep learning models, particularly LSTM, outperform traditional methods by capturing complex, nonlinear patterns in the data, resulting in ...

22 окт. 2024 г. · This paper proposes three types of recurrent neural network (RNN) algorithms used to predict the prices of three types of cryptocurrencies.

27 мар. 2022 г. · Forecasting Cryptocurrency Prices Using LSTM, GRU, and Bi-Directional LSTM: A Deep Learning Approach. Article. Full-text available. Feb 2023.

5 окт. 2023 г. · Forecasting Cryptocurrency Prices Using LSTM, GRU, and Bi-Directional LSTM: A Deep Learning Approach. Phumudzo Seabe et al. Fractal Fract ...

For cryptocurrency price forecasting, the LSTM and GRU neural networks are the most widely used. RNNs, equipped with a self-feedback mechanism, have the ...

Results obtained from these models show that the gated recurrent unit (GRU) performed better in prediction for all types of cryptocurrency than the long short- ...