摘要
针对医疗机构中日趋复杂化的财务数据难以被快速、及时地分析处理等问题,文中基于深度数据挖掘技术,通过对财务数据的特征进行识别,设计实现了一套高效的财务数据分析算法。为提高财务数据的安全性与正则化程度,该平台采用区块链技术完成了财务数据的高维表征。同时,利用神经网络设计数据挖掘算法有效解决了高维财务数据的识别与分类问题。数据实验结果表明,文中所提算法与常用数据分析算法相比,其准确度可达99.2%,能够对不同时间跨度的财务数据进行精准分析。
In view of the increasingly complex financial data in medical institutions is difficult to be analyzed and processed quickly and timely,this paper designs and implements a set of efficient financial data analysis algorithm based on deep data mining technology and through the identification of the characteristics of financial data. In order to improve the security and regularization of financial data,the platform uses blockchain technology to complete the high-dimensional representation of financial data. At the same time,neural network is used to design data mining algorithm to effectively solve the problem of recognition and classification of high-dimensional financial data. The experimental results show that the accuracy of the proposed algorithm can reach 99.2% compared with the common data analysis algorithms,and it can accurately analyze the financial data of different time spans.
作者
郭宁
龚致富
GUO Ning;GONG Zhifu(The First Affiliated Hospital of Hebei North University,Zhangjiakou 075000,China)
出处
《电子设计工程》
2023年第5期46-50,共5页
Electronic Design Engineering
基金
河北省卫生厅2020年度河北省医学科学研究课题计划(20200563)
张家口市2022年度社会科学研究项目(2022057)。
关键词
数据挖掘
特征识别
区块链技术
神经网络
data mining
feature recognition
blockchain technology
neural network
