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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Main Author: Lin Shiyu
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
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.
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institution Kabale University
issn 2261-2424
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publishDate 2025-01-01
publisher EDP Sciences
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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