科研成果详情

题名Intelligent flow detection in hospital microservices platform security operation and maintenance management system based on genetic algorithm optimized LightGBM algorithm
其他题名基于遗传算法优化 LightGBM 算法的医院微服务平台安全运维管理系统的流量智能化检测
作者
发表日期2024-06
发表期刊Chinese Journal of Medical Physics   影响因子和分区
语种中文 ; 英语
原始文献类型Article
关键词genetic algorithm LightGBM microservices platform operation and maintenance management system
其他关键词microservices platform ; operation and maintenance management system ; genetic algorithm ; LightGBM
摘要

A novel data detection algorithm is proposed to improve the data detection efficiency of the operation and maintenance management system for the hospital microservices platform. Based on the multiple characteristics of the platform data, the algorithm constructs the overall framework of the operation and maintenance management system. By combining the parameter optimization ability of genetic algorithm and the rapid detection ability of LightGBM algorithm, the effective detection of the flow data in the operation and maintenance management system is realized. The effectiveness of the model is verified through a control test, and the results show that the proposed method performs the best in intelligent flow detection, achieving accuracy of 0.981 0, recall rate of 0.68 and F1 value of 0.77 which are all higher than those of the traditional methods.

其他摘要A novel data detection algorithm is proposed to improve the data detection efficiency of the operation and maintenance management system for the hospital microservices platform.Based on the multiple characteristics of the platform data,the algorithm constructs the overall framework of the operation and maintenance management system.By combining the parameter optimization ability of genetic algorithm and the rapid detection ability of LightGBM algorithm,the effective detection of the flow data in the operation and maintenance management system is realized.The effectiveness of the model is verified through a control test,and the results show that the proposed method performs the best in intelligent flow detection,achieving accuracy of 0.981 0,recall rate of 0.68 and F1 value of 0.77 which are all higher than those of the traditional methods.
资助项目Y20211158:温州市基础性科研项目;2020No.78:省部级5G+医疗健康应用试点项目;2016E10011:浙江省智慧医疗工程技术研究中心项目
出版者Editorial Department of Chinese Journal of Medical Physics
ISSN1005-202X
卷号41期号:6页码:788-792
DOI10.3969/j.issn.1005-202X.2024.06.019
页数5
收录类别SCOPUS ; 万方 ; ISTIC ; CSCD
URL查看原文
SCOPUSEID2-s2.0-85197297197
Scopus学科分类Radiology, Nuclear Medicine and Imaging;Biophysics
引用统计
文献类型期刊论文
条目标识符https://kms.wmu.edu.cn/handle/3ETUA0LF/215628
专题附属第一医院
第一临床医学院(信息与工程学院)、附属第一医院
作者单位
Department of Medical Information,The First Affiliated Hospital of Wenzhou Medical University,Wenzhou,325000,China
第一作者单位附属第一医院;  第一临床医学院(信息与工程学院)、附属第一医院
第一作者的第一单位附属第一医院
推荐引用方式
GB/T 7714
Zhuo, Yichao,Hao, Haibin. Intelligent flow detection in hospital microservices platform security operation and maintenance management system based on genetic algorithm optimized LightGBM algorithm[J]. Chinese Journal of Medical Physics,2024,41(6):788-792.
APA Zhuo, Yichao, & Hao, Haibin. (2024). Intelligent flow detection in hospital microservices platform security operation and maintenance management system based on genetic algorithm optimized LightGBM algorithm. Chinese Journal of Medical Physics, 41(6), 788-792.
MLA Zhuo, Yichao,et al."Intelligent flow detection in hospital microservices platform security operation and maintenance management system based on genetic algorithm optimized LightGBM algorithm".Chinese Journal of Medical Physics 41.6(2024):788-792.

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