Blockchain Equity System Transaction Method and System Research Based on Machine Learning and Big Data Algorithm

Kanghua Peng

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Blockchain Equity System Transaction Method and System Research Based on Machine Learning and Big Data Algorithm

机译：基于机器学习和大数据算法的区块链股权系统交易方法与系统研究

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With the development of machine learning and big data, traditional equity trading system methods can no longer meet the current trading needs, and there are still problems such as low operating efficiency and serious homogeneity. Blockchain technology has the characteristics of decentralization and can also complete transactions through smart contracts, innovating the way of equity system transactions. The purpose of this paper is to build an equity trading system in combination with blockchain in the context of machine learning and big data and provide innovative trading methods, so as to provide reference and reference significance for the construction of my country’s equity market. This article uses literature data method, comparative analysis method, factor analysis method, and other methods to carry out research, in-depth study of machine learning and big data, blockchain-related concepts, system composition, application situation, etc., and discusses the allocation of equity trading market The functions of resources, risk diversification, risk transfer, price determination, etc., have built a blockchain equity trading system, designed a consensus mechanism, block generation protocol, block verification, decentralization, and smart contract platform, and finally conducted a national equity transaction the background of the market is analyzed, and the experimental results, simulation indicators, transaction time, transmission consumption, and other content of the system constructed in this article are analyzed. In the single-node test, the CPU usage of the PoW consensus mechanism algorithm reached 100%, but the improved PBFT consensus mechanism was only 16%, which saved a lot of computing power and improved computing performance.

机译：随着机器学习和大数据的发展，传统的股票交易系统的方法已经不能满足目前的交易需求，而且还存在如运行效率低和同质化严重的问题。 Blockchain技术具有分权的特点，还可以通过智能合同完成交易，创新产权制度的交易方式。本文的目的是在机器学习和大数据的背景下构建相结合的股权交易系统blockchain并提供创新的交易方式，以提供对我国资本市场建设的借鉴和参考意义。本文采用文献资料法，比较分析法，因子分析法等方法进行研究，深入学习机和大数据的研究，blockchain相关的概念，系统组成，应用情况等，并讨论股权交易市场的资源配置，分散风险，风险转移，价格确定等功能，都建有blockchain股权交易系统，设计了一个共识机制，块生成协议，块验证，权力下放，以及智能平台的合同，最后进行的全国股权交易市场的背景进行了分析，实验结果，仿真指标，交易时间，传输消耗，本文构建了系统的其他内容进行了分析。在单节点测试，战俘共识机构算法的CPU使用率达到100％，但改进的PBFT共识机构只有16％，这节省了大量的计算能力和改进的计算性能。

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《Wireless communications & mobile computing》 |2021年第a期|共14页
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Kanghua Peng;
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Blockchain Equity System Transaction Method and System Research Based on Machine Learning and Big Data Algorithm

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