Enhancing African market predictions: Integrating quantum computing with Echo State Networks

IF 2.7 Q2 MULTIDISCIPLINARY SCIENCES Scientific African Pub Date : 2024-06-29 DOI:10.1016/j.sciaf.2024.e02299
Soukaina Seddik , Hayat Routaib , Abdelali Elmounadi , Anass El Haddadi
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Abstract

The integration of Quantum Computing into Echo State Networks (ESN) materializes in the form of the Quantum Echo State Network (QESN), a methodological innovation that reshapes predictive analytics within the domain of artificial intelligence. This investigation harnesses the novel QESN model alongside traditional ESNs, deploying them within the dynamic and burgeoning financial market of Africa. Our focus zeroes in on the Google Stock Price dataset, which provides a rich tapestry of regional financial activity. The QESN model distinguishes itself by a complex interconnection of qubits that conduct quantum operations, offering a marked amplification of computational capability. The empirical analysis reveals that the QESN model’s predictive prowess substantially exceeds that of its ESN counterpart, achieving an unprecedentedly low Mean Squared Error (MSE) of 0.00021 in forecasting market trends. This exceptional figure redefines the standards of financial prediction models in African markets and establishes the QESN as an instrumental breakthrough, providing unparalleled accuracy in the analysis and prediction of financial data.

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加强非洲市场预测:将量子计算与回声状态网络相结合
量子计算与回声状态网络(ESN)的整合以量子回声状态网络(QESN)的形式实现,这是一种方法创新,重塑了人工智能领域的预测分析。这项研究将新颖的 QESN 模型与传统的 ESN 结合起来,并将其应用于非洲充满活力的新兴金融市场。我们的重点是谷歌股票价格数据集,该数据集提供了丰富的地区金融活动信息。QESN 模型的与众不同之处在于,它通过复杂的量子比特互连来进行量子运算,从而显著增强了计算能力。实证分析表明,QESN 模型的预测能力大大超过 ESN 模型,在预测市场趋势方面达到了前所未有的 0.00021 平均平方误差 (MSE)。这一非凡数据重新定义了非洲市场金融预测模型的标准,并将 QESN 确立为一项工具性突破,为金融数据的分析和预测提供了无与伦比的准确性。
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来源期刊
Scientific African
Scientific African Multidisciplinary-Multidisciplinary
CiteScore
5.60
自引率
3.40%
发文量
332
审稿时长
10 weeks
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