Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance
Traditional financial prediction models are difficult to cope with complex financial markets, especially cryptocurrency markets. In this paper, a quantum finance-based temporal chaotic neural oscillatory network (TSCNON) prediction model is used for the first time to predict the share price of Bitco...
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| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | SHS Web of Conferences |
| Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2025/09/shsconf_icdde2025_02025.pdf |
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| author | Lin Shiyu |
| author_facet | Lin Shiyu |
| author_sort | Lin Shiyu |
| collection | DOAJ |
| description | Traditional financial prediction models are difficult to cope with complex financial markets, especially cryptocurrency markets. In this paper, a quantum finance-based temporal chaotic neural oscillatory network (TSCNON) prediction model is used for the first time to predict the share price of Bitcoin by combining the quantum price level (QPL) technique with the theory of chaotic neural networks. Based on quantum field signalling (QFS) and Lee oscillator, the overfitting and deadlocking problems of traditional neural networks when dealing with large-scale financial data are solved. The structural design of the TSCNON model and its training algorithm are presented. The application framework of TSCNON in Bitcoin price prediction is demonstrated. Experimental results show that the TSCNON model can greatly reduce the prediction error and improve the prediction accuracy. This paper provides financial market participants with more accurate and reliable prediction tools and promotes the promotion of quantum financial technology in practical applications. |
| format | Article |
| id | doaj-art-e1a43d986f234f45b7a067f5517869bb |
| institution | Kabale University |
| issn | 2261-2424 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | SHS Web of Conferences |
| spelling | doaj-art-e1a43d986f234f45b7a067f5517869bb2025-08-20T03:31:36ZengEDP SciencesSHS Web of Conferences2261-24242025-01-012180202510.1051/shsconf/202521802025shsconf_icdde2025_02025Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum FinanceLin Shiyu0Faculty of Science and Technology, Beijing Normal-Hong Kong Baptist UniversityTraditional financial prediction models are difficult to cope with complex financial markets, especially cryptocurrency markets. In this paper, a quantum finance-based temporal chaotic neural oscillatory network (TSCNON) prediction model is used for the first time to predict the share price of Bitcoin by combining the quantum price level (QPL) technique with the theory of chaotic neural networks. Based on quantum field signalling (QFS) and Lee oscillator, the overfitting and deadlocking problems of traditional neural networks when dealing with large-scale financial data are solved. The structural design of the TSCNON model and its training algorithm are presented. The application framework of TSCNON in Bitcoin price prediction is demonstrated. Experimental results show that the TSCNON model can greatly reduce the prediction error and improve the prediction accuracy. This paper provides financial market participants with more accurate and reliable prediction tools and promotes the promotion of quantum financial technology in practical applications.https://www.shs-conferences.org/articles/shsconf/pdf/2025/09/shsconf_icdde2025_02025.pdf |
| spellingShingle | Lin Shiyu Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance SHS Web of Conferences |
| title | Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance |
| title_full | Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance |
| title_fullStr | Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance |
| title_full_unstemmed | Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance |
| title_short | Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance |
| title_sort | predicting bitcoin prices using time series chaotic neural oscillatory networks tscnon in quantum finance |
| url | https://www.shs-conferences.org/articles/shsconf/pdf/2025/09/shsconf_icdde2025_02025.pdf |
| work_keys_str_mv | AT linshiyu predictingbitcoinpricesusingtimeserieschaoticneuraloscillatorynetworkstscnoninquantumfinance |