基于深度学习的电脑主机缺陷检测系统设计  

Design of a Computer Host Defect Detection System Based on Deep Learning

作　　者：张建粉 李宇昕 杨阳 Zhang Jianfen;Li Yuxin;Yangyang(Bazhou Power Supply Company,State Grid Xinjiang Power Co.,Ltd.,Xinjiang 830000,China)

机构地区：[1]国网新疆电力有限公司巴州供电公司,新疆830000

出　　处：《办公自动化》2025年第3期106-108,共3页Office Informatization

摘　　要：文章提出一种基于深度学习的电脑主机缺陷监测系统设计。该系统利用互联网+信息技术,结合深度学习法,实现对电脑主机运行状态的实时监测和缺陷预测。通过对大量历史数据的训练和学习,系统能自动识别出电脑主机的潜在缺陷,并提供相应的维护建议,从而提高电脑主机的稳定性和可靠性。文章首先介绍深度学习在计算机视觉和自然语言处理等领域的应用背景,然后,详细阐述基于深度学习的电脑主机缺陷监测系统的设计思路、技术实现和实验结果。最后,对系统的应用前景进行展望。This paper proposes the design of a computer host defect detection system based on deep learning.The system leverages Internet+information technology and deep learning methods to achieve real-time monitoring and defect prediction for computer hosts.By training and learning from a large amount of historical data,the system can automatically identify potential defects in computer hosts and provide corresponding maintenance suggestions,thereby enhancing the stability and reliability of the systems.The paper first introduces the application background of deep learning in fields such as computer vision and natural language processing.It then elaborates on the design concept,technical implementation,and experimental results of the computer host defect detection system based on deep learning.Finally,it provides an outlook on the application prospects of the system.

关 键 词：深度学习 电脑主机 缺陷监测 互联网+信息技术 实时监测 

分 类 号：TP311.52[自动化与计算机技术—计算机软件与理论]