Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach
- Title
- Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach
- Description
- 2023 4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023 - Proceedings pp.953-958
- Creator
- Karahyla J.K.; Sharma N.; Chamoli S.; Shirgire A.; Kant R.; Chauhan A.
- Source
- <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168306900&doi=10.1109%2fICESC57686.2023.10193561&partnerID=40&md5=a89c84b43b94652e3f282ec9a0e67182" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168306900&doi=10.1109%2fICESC57686.2023.10193561&partnerID=40&md5=a89c84b43b94652e3f282ec9a0e67182</a>
- Date
- 2023-01-01
Collection
Citation
Karahyla J.K.; Sharma N.; Chamoli S.; Shirgire A.; Kant R.; Chauhan A., “Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 8, 2025, https://archives.christuniversity.in/items/show/10245.