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- Vol. 6 Issue 2
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Advanced Predictive Analytics for volatile cryptocurrency markets
Authors
1 2 3 Department of Computer Science Engineering, Sathyabhma Institute of Science and Technology, Chennai, Tamil Nadu, India.
Article Information
- Published In
- Volume 6, Issue 2 (2026)
- Published Online
- March-April 2026
- Pages
- 104-111
- Article Type
- Original Article
- Check for updates
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References
1. Amin Armin, Amin Shiri and Bahrak Bahrak, Comparison of Machine Learning Method Cryptocurrency Price Prediction in 2022 8th Iranian International Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran, 2022, pp 1-6, doi: 10.1109/ICSPIS56952.2022.10043898.
2. V.S. Shah and R. S. Kute, Cryptocurrency Price Prediction using Graph Embedding and Deep Learning, in 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 567 -571, doi: 10.1109/ICAC3N56670.2022.10074113.
3. by R. Parekh et al. focuses on the topic of predicting cryptocurrencies using deep learning and sentiment analysis technology. <|human|>The author of the article [3] is R. Parekh et al. and the article deals with the issue of cryptocurrencies price forecasting with the help of deep learning and sentiment analysis technology.
4. A. Tanwar and V. Kumar, Cryptocurrency Prices: Prediction with Transformers and Long Short-Term Neural Networks, International Conference on Intelligent Controller and Computing Smart Power, IEEE, 2022, Hyderabad, India, 2022, pp. 1 - 4, doi: 10.1109/ICICCSP53532.2022.9862436.
5. T. Mahmud, T. Akter, R. Chakma, T. Barua, M. S. Hossain, and K. Andersson, "Cryptocurrency Price Prediction with machine learning algorithms," 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kamand, India, 2024, pp. 1--6, doi: 10.1109/ICCCNT61001.2024.107239
6. A. Mashatan, M. S. Sangari and M. Dehghani, "The effect of information privacy and information security perceptions on consumer trust in crypto- payment: an empirical study," in IEEE Access, vol. 10, pp. 6944169454, 2022.
7. The article by A. F. M. S. Shah, M. A. Karabulut, A. F. M. S. Akhter, N. Mustari, A. K. Pathan, K. M. Rabie, and T. Shongwe focuses on the crucial aspects and features of cryptocurrency and provides a survey, IEEE Access, vol. 11, pp. 9451-9468, 2023.
8. Garg G, Kataria P, Durgapal P, Anand AS, and Garg G, "A Comprehensive Distributed Framework of Cross-Silo Federated Learning with Blockchain," in Proc. 5th Int. Conf. Blockchain Comput. Appl. (BCCA), Oct. 2023, pp. 538–545.
9. A. P. Kalapaaking, I. Khalil, M. S. Rahman, M. Atiquzzaman, X. Yi and M. Almashor, "Blockchain-Based Federated Learning with Secure Aggregation in Trusted Environment of Internet-of-Things," IEEE Trans. Ind. Informat., vol. 19, no. 2, pp. 1703-1714, Feb. 2023.
10. Hu, Z. Wang, M. Xu, and X. Cheng, Blockchain and Federated Edge Learning to Privacy-Preserving Mobile Crowdsensing, IEEE Internet Things J., vol. 10, no. 14, pp. 12000-12011, Sep. 2023.
2. V.S. Shah and R. S. Kute, Cryptocurrency Price Prediction using Graph Embedding and Deep Learning, in 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 567 -571, doi: 10.1109/ICAC3N56670.2022.10074113.
3. by R. Parekh et al. focuses on the topic of predicting cryptocurrencies using deep learning and sentiment analysis technology. <|human|>The author of the article [3] is R. Parekh et al. and the article deals with the issue of cryptocurrencies price forecasting with the help of deep learning and sentiment analysis technology.
4. A. Tanwar and V. Kumar, Cryptocurrency Prices: Prediction with Transformers and Long Short-Term Neural Networks, International Conference on Intelligent Controller and Computing Smart Power, IEEE, 2022, Hyderabad, India, 2022, pp. 1 - 4, doi: 10.1109/ICICCSP53532.2022.9862436.
5. T. Mahmud, T. Akter, R. Chakma, T. Barua, M. S. Hossain, and K. Andersson, "Cryptocurrency Price Prediction with machine learning algorithms," 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kamand, India, 2024, pp. 1--6, doi: 10.1109/ICCCNT61001.2024.107239
6. A. Mashatan, M. S. Sangari and M. Dehghani, "The effect of information privacy and information security perceptions on consumer trust in crypto- payment: an empirical study," in IEEE Access, vol. 10, pp. 6944169454, 2022.
7. The article by A. F. M. S. Shah, M. A. Karabulut, A. F. M. S. Akhter, N. Mustari, A. K. Pathan, K. M. Rabie, and T. Shongwe focuses on the crucial aspects and features of cryptocurrency and provides a survey, IEEE Access, vol. 11, pp. 9451-9468, 2023.
8. Garg G, Kataria P, Durgapal P, Anand AS, and Garg G, "A Comprehensive Distributed Framework of Cross-Silo Federated Learning with Blockchain," in Proc. 5th Int. Conf. Blockchain Comput. Appl. (BCCA), Oct. 2023, pp. 538–545.
9. A. P. Kalapaaking, I. Khalil, M. S. Rahman, M. Atiquzzaman, X. Yi and M. Almashor, "Blockchain-Based Federated Learning with Secure Aggregation in Trusted Environment of Internet-of-Things," IEEE Trans. Ind. Informat., vol. 19, no. 2, pp. 1703-1714, Feb. 2023.
10. Hu, Z. Wang, M. Xu, and X. Cheng, Blockchain and Federated Edge Learning to Privacy-Preserving Mobile Crowdsensing, IEEE Internet Things J., vol. 10, no. 14, pp. 12000-12011, Sep. 2023.
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