Sports training big data integration and optimization based on block-chain technology

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-06-04 DOI:10.3233/JIFS-219115

Zhichen Yang, Xinxin Zheng

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Abstract

The increasing maturity of Internet information technology has led to the rapid rise of block-chain technology. In essence, the block-chain is a shared database. In recent years, block-chain technology has attracted the attention of the public and society. This paper mainly conducts systematic research and analysis on the integration and optimization of big data in sports training by block-chain, and achieves large-scale consensus in the case of decentralization, therefore, the information of the network will not be tampered with and forged, thus crossing the boundary of the bottom layer of the information system. This paper is based on the integration and optimization of sports training is big data. With the help of block-chain technology, each module is designed and implemented according to the needs. At the same time, the pow algorithm inside the block-chain is improved. The research results show that it is based on the block-chain. The integration and optimization of technical sports training big data can reduce the number of sports training injuries of sports school students by 10% -20%, which is very conducive to the healthy growth and development of sports school students.

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基于区块链技术的运动训练大数据整合与优化

互联网信息技术的日益成熟，使得区块链技术迅速崛起。从本质上讲，区块链是一个共享数据库。近年来，区块链技术引起了公众和社会的广泛关注。本文主要对区块链对运动训练大数据的整合与优化进行系统的研究与分析，在去中心化的情况下达成大规模的共识，网络的信息不会被篡改和伪造，从而跨越信息系统底层的边界。本文基于运动训练大数据的整合与优化。借助区块链技术，根据需求设计和实现各个模块。同时对区块链内部的pow算法进行了改进。研究结果表明，它是基于区块链的。技术运动训练大数据的整合和优化，可以使体校学生的运动训练损伤数量减少10% -20%，非常有利于体校学生的健康成长和发展。

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来源期刊

International Journal of Fuzzy Logic and Intelligent Systems COMPUTER SCIENCE, THEORY & METHODS-

CiteScore

2.80

自引率

23.10%

发文量

期刊介绍： The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.