Combining Blockchain and Machine Learning to Forecast Cryptocurrency Prices

K. Martin, I. Alsmadi, M. Rahouti, M. Ayyash
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引用次数: 2

Abstract

Blockchain is an emerging technology that enables a vital framework for various cryptocurrency operations such as bitcoin. Notably, without any involvement from third party authorities, blockchain offers a decentralized consensus scheme to process user transactions, fund transfer, and various data records in a secure and reliable way. Furthermore, bitcoin price forecasting has been a vital research trend, where machine learning techniques play a substantial role. A sophisticated and appropriately trained model can be useless if the features being tested are unreliable. Independently, one of the most desirable aspects of a system that utilizes the blockchain is the concrete objectiveness by which each entry is cataloged. Any data collected and reported on the blockchain is unambiguous, and therefore, extremely suitable for a machine learning algorithm. To efficiently forecast bitcoin price movements, in this work, we propose and examine various lenses by which to view this union, each with varying degrees of success.
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结合区块链和机器学习预测加密货币价格
区块链是一种新兴技术,为比特币等各种加密货币操作提供了重要框架。值得注意的是,在没有第三方机构参与的情况下,区块链提供了一个分散的共识方案,以安全可靠的方式处理用户交易、资金转移和各种数据记录。此外,比特币价格预测一直是一个重要的研究趋势,机器学习技术在其中发挥着重要作用。如果被测试的特征是不可靠的,那么一个复杂且经过适当训练的模型可能是无用的。独立地说,使用区块链的系统最理想的方面之一是对每个条目进行编目的具体客观性。区块链上收集和报告的任何数据都是明确的,因此非常适合机器学习算法。为了有效地预测比特币的价格走势,在这项工作中,我们提出并研究了各种镜头,通过这些镜头来观察这种结合,每种镜头都取得了不同程度的成功。
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Coordinated Landmark-based Routing for Blockchain Offline Channels A Blockchain Based Decentralized Computing And NFT Infrastructure For Game Networks Improving the performance of the Proof-of-Work Consensus Protocol Using Machine learning OraclesLink: An architecture for secure oracle usage BCCA 2020 Preface
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