关于大数据时代高校科研管理创新的思考

Sci. Program. Pub Date : 2022-01-11 DOI:10.1155/2022/7674486
Yiming Li
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引用次数: 3

摘要

在中国,大学是重要的科研和创新中心,科研管理的质量对大学创新有着重要的影响。高校管理信息化是大数据环境下高校发展的重要组成部分。因此,如何改进SR管理是至关重要的。因此,本文基于大数据技术构建了一个B/W/D/C (Browser/Web/Database/Client)四层的高校SR管理创新信息系统,并对系统的硬件和软件配置进行了深入研究。提出了SVM-WNB(支持向量机加权NB)分类算法,改进后的算法在Hadoop云计算平台上并行运行,使算法能够高效处理大量数据。根据大量的仿真实验和真实的多数据中心环境实验,本文提出的优化策略可以有效地优化科学大数据应用的执行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reflections on the Innovation of University Scientific Research Management in the Era of Big Data
In China, universities are important centers for SR (scientific research) and innovation, and the quality of SR management has a significant impact on university innovation. The informatization of SR management is a critical component of university development in the big data environment. As a result, it is crucial to figure out how to improve SR management. As a result, this paper builds a four-tier B/W/D/C (Browser/Web/Database/Client) university SR management innovation information system based on big data technology and thoroughly examines the system’s hardware and software configuration. The SVM-WNB (Support Vector Machine-Weighted NB) classification algorithm is proposed, and the improved algorithm runs in parallel on the Hadoop cloud computing platform, allowing the algorithm to process large amounts of data efficiently. The optimization strategy proposed in this paper can effectively optimize the execution of scientific big data applications according to a large number of simulation experiments and real-world multidata center environment experiments.
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