基于人工智能的企业项目云数据自动化共享系统  

Artificial intelligence⁃based cloud data automation sharing system for enterprise projects

作　　者：郑肖 蒋磊 朱挺 刘亚强 ZHENG Xiao;JIANG Lei;ZHU Ting;LIU Yaqiang(Ningbo Mengchuang Information Technology Co.,Ltd.,Ningbo 315000,China)

机构地区：[1]宁波梦创信息科技有限公司,浙江宁波315000

出　　处：《电子设计工程》2025年第5期59-64,共6页Electronic Design Engineering

摘　　要：研究主要针对当前企业项目云数据共享效果不佳,隐私性不足的问题,利用基于人工智能的方法搭建了一个云数据自动化共享系统。新系统使用联邦学习和差分隐私算法提升了算法性能。通过使用表明,新系统的基准测试准确率范围能够达到89.24%~91.54%。同时新系统的准确率最高能够达到98.42%。新系统的模型交易延时最高能够达到964.48 ms。由此可见,该文模型能够有效提升云数据共享准确性,同时加入联邦学习也能够提升云数据共享效果。The research focuses on the current problems of poor cloud data sharing and lack of privacy in enterprise projects,and builds an automated cloud data sharing system through anartificial intelligence-based approach.The new system uses federated learning and differential privacy algorithms to enhance the performance of the algorithm.It is shown through usage that the new system is able to achieve a benchmarking accuracy range of 89.24%~91.54%.At the same time,the new system is able to achieve an accuracy of up to 98.42%.The model transaction latency of the new system can reach a maximum of 964.48 ms.This shows that the research use model can effectively improve the accuracy of cloud data sharing,and the addition of federated learning can also improve the effectiveness of cloud data sharing.

关 键 词：人工智能 云数据 共享 联邦学习 

分 类 号：TN0[电子电信—物理电子学]