Bitcoin Prediction Based on OSL-SCN and Conformal Prediction Method
Bitcoin, as the most widely recognized cryptocurrency, has attracted significant global attention from businesses, consumers, and investors. This study introduces a hybrid model that integrates an online self-learning stochastic configuration network (OSL-SCN) with conformal prediction. The model autonomously adjusts its parameters in response to real-time data.Predictions from the OSL-SCN are refined through conformal prediction, which generates confidence intervals to enhance reliability. The results, using historical Bitcoin prices from Wikipedia, demonstrate that the combined approach enhances both prediction accuracy and reliability.
Authors
- Kaimeng Li
- Xiangyu Zhang (ORCID: https://orcid.org/0009-0008-9539-8061)
- Wenjing Wang (ORCID: https://orcid.org/0009-0006-7638-0478)
Institutions
- Linyi University (CN)
Publication Details
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1109/icftic64248.2024.10913417
- Citations
- 1
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.27