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引用本文:韦群锋,祁 斌.融合大数据的校园公权力监督机制研究与模型构建[J].软件工程,2024,(2):74-78.【点击复制】
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融合大数据的校园公权力监督机制研究与模型构建
韦群锋, 祁 斌
(浙江工商职业技术学院电子信息学院, 浙江 宁波 315010)
20820047@zbti.edu.cn; qibingood@gmail.com
摘 要: 通过运用大数据技术,构建了一种校园公权力监督模型(CPASM),旨在提升教育资源配置的透明度和公平性,以及优化教学与行政决策。利用案例分析法,聚焦于A学院计算机应用技术专业,探讨了大数据在财务管理、教学质量评估和行政决策过程中的应用。CPASM模型结合时间序列分析和外部因素分析,应用自回归积分滑动平均(ARIMA)模型处理数据,同时将校园公权力动态变化纳入考量。CPASM模型的拟合与验证结果表明,其预测的均方误差(MSE)、均方根误差(RMSE)较低,确定系数(R2)接近1,准确地描绘了财务趋势,有助于管理层进行财务规划和资源配置。
关键词: 校园公权力监督;大数据;教育管理;监督模型
中图分类号: TP393.2    文献标识码: A
基金项目: 2023年度第二批宁波市哲社规划课题(G2023-2-Z01)
Research and Model Development of a Big Data-integrated Campus Public Authority Supervision Mechanism
WEI Qunfeng, QI Bin
(College of Electronic Inf ormation, Zhejiang Business Technology Istitute, Ningbo 315010, China)
20820047@zbti.edu.cn; qibingood@gmail.com
Abstract: With big data technology, this paper proposes to develop a Campus Public Authority Supervision Model (CPASM), with the objective of enhancing the transparency and fairness of educational resource allocation, as well as optimizing teaching and administrative decision-making processes. Taking the Computer Application Technology major of College A as a real case, this research discusses the application of big data in financial management, teaching quality assessment, and administrative decision-making. The CPASM model integrates time series analysis with external factor analysis, employs the Autoregressive Integrated Moving Average (ARIMA) model for data processing, and takes into account of the dynamics of campus authority. The fitting and validation results of the CPASM model indicate that its predicted Mean Square Error (MSE) and Root Mean Square Error ( RMSE) are comparatively low, and the Coefficient of Determination (R2 ) approaches 1. The model accurately depicts financial trends and assists management in financial planning and resource allocation.
Keywords: campus public authority supervision; big data; educational management; supervision model


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