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This is a Experimental Study study.

October 20, 2025Management0 citationsOpen Access

Hybrid CNN-BiLSTM-Attention Framework Enhances Cryptocurrency Price Prediction

Cryptocurrency Price Prediction and Investment Decision Support Using a Transfer Learning-Based Hybrid CNN-BiLSTM-Attention Deep Learning Framework

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Transfer learning improves investment decision support in cryptocurrency, indicating strong predictive capabilities.

The proposed framework achieves an overall accuracy of 96%, demonstrating significant predictive power.
In evaluations, the hybrid model outperforms standalone CNN, LSTM, and RNN architectures with an F1 score of 95.5%.
Utilizing a historical dataset of major cryptocurrencies, the model integrates CNN and BiLSTM for effective analysis.
This reliable tool aids investors and financial professionals in making informed decisions in a volatile market.

Durga et al. (2025) studied this question.

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October 20, 2025Management0 citationsOpen Access

Cryptocurrency Price Prediction and Investment Decision Support Using a Transfer Learning-Based Hybrid CNN-BiLSTM-Attention Deep Learning Framework

View Full Paper

Ask AI

Bookmark

Authors

Transfer learning improves investment decision support in cryptocurrency, indicating strong predictive capabilities.

The proposed framework achieves an overall accuracy of 96%, demonstrating significant predictive power.
In evaluations, the hybrid model outperforms standalone CNN, LSTM, and RNN architectures with an F1 score of 95.5%.
Utilizing a historical dataset of major cryptocurrencies, the model integrates CNN and BiLSTM for effective analysis.
This reliable tool aids investors and financial professionals in making informed decisions in a volatile market.

Durga et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark