摘要
针对电力生产安全,研究了基于人工智能深度学习算法的电力安全知识学习系统,设计了电力安全知识学习应用系统。采用Docker平台为用户提供更多的计算资源,具有隔离性、可配额、移动性和安全性的优点,实现了电力安全知识学习应用的分模块管理。还研究了电力安全知识学习移动App客户端,在Android和iOS 2种操作系统下,员工可随时随地学习,并且不受手机类型限制。利用图谱实体对齐算法,实现了用户对电力安全知识的学习。为了验证研究的系统实用性,进行了相关实验。实验中测得该系统同时在线人数可达到3000人左右,测试过程中还测试了系统性能,显示了学习方法的多样性,系统界面的完整性以及电力安全知识分类的整齐清晰。
In view of the safety risks in electric power production,this study investigates the power safety knowledge learning system based on artificial intelligence deep learning algorithms and designs the power safety knowledge learning application system.By using the Docker platform,users are provided with more computing resources,which possess the advantages of isolation,quota,mobility,and security,and enable the modular management of power safety knowledge learning and application.Furthermore,this paper studies the mobile APP client for power safety knowledge learning and designs it for both Android and iOS operating systems,allowing employees to learn safety knowledge anytime and anywhere without being limited by the type of mobile system.Finally,the graph entity alignment algorithm is employed to facilitate users’learning of power safety knowledge.To verify the practicality of the system,relevant experiments have been conducted.The experiment shows that the system can accommodate about 3000 users online simultaneously,and the system performance is tested during the process,demonstrating the diversity of learning methods,the completeness of the system interface,and the neatly organized classification of power safety knowledge.
作者
李媛
张志荣
杨晶
蒋万珊
王茜
李施润
LI Yuan;ZHANG Zhirong;YANG Jing;JIANG Wanshan;WANG Qian;LI Shirun(Yuxi Power Supply Bureau of Yunnan Power Grid Corporation,Yuxi 653100,China)
出处
《微型电脑应用》
2023年第4期164-167,共4页
Microcomputer Applications
