大数据驱动的计算机实验室信息化管理系统技术优化研究

Research on Technical Optimization of Big-Data-Driven Informatization Management System for Computer Laboratories

摘要: 针对高校计算机实验室现有管理系统中资源调度分散、设备维护滞后和数据整合不足等问题，本文以XX大学计算机实验室为研究对象，提出大数据驱动的信息化管理系统优化方案。研究通过构建统一数据域，引入协同过滤资源调度模型、孤立森林异常识别机制和多源数据融合分析模块，实现预约、设备、维修和资产数据的贯通管理。结果表明，优化后资源利用率由65%提升至92%，故障响应时间由24 h缩短至1.5 h，数据整合率由50%提升至100%，预约成功率提升至95%。该方案能够有效增强实验室资源配置效率、设备运维能力和管理决策水平，具有一定推广价值。

Abstract: Aiming at the problems existing in the current management systems of university computer laboratories, such as decentralized resource scheduling, delayed equipment maintenance and insufficient data integration, this paper takes the computer laboratory of XX University as the research object and proposes an optimization scheme for a big-data-driven informatization management system. By constructing a unified data domain, this research introduces a collaborativefiltering resource scheduling model, an isolation-forest anomaly identification mechanism and a multi-source data fusion analysis module to realize integrated management of appointment, equipment, maintenance and asset data. The experimental results show that after optimization, the resource utilization rate increases from 65% to 92%, the fault response time is shortened from 24 h to 1.5 h, the data integration rate rises from 50% to 100%, and the appointment success rate reaches 95%. The proposed scheme can effectively improve laboratory resource allocation efficiency, equipment operationandmaintenance capability and managementdecisionmaking level, and possesses certain promotion value.