工业加热2024,Vol.53Issue(3) :59-63.DOI:10.3969/j.issn.1002-1639.2024.03.014

基于数据挖掘的电炉企业财务数据分类管理系统设计

Design of Electric Furnace Enterprise Financial Data Classification Management System Based on Data Mining

王冠卓 刘大旭 孙聪
工业加热2024,Vol.53Issue(3) :59-63.DOI:10.3969/j.issn.1002-1639.2024.03.014

基于数据挖掘的电炉企业财务数据分类管理系统设计

Design of Electric Furnace Enterprise Financial Data Classification Management System Based on Data Mining

王冠卓 1刘大旭 1孙聪1
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作者信息

  • 1. 黑龙江中医药大学,黑龙江 哈尔滨 150040
  • 折叠

摘要

为提升电炉企业财务数据处理效率、提高财务数据分类管理效果,本文研究提出并设计出了一种基于数据挖掘的财务数据分类管理系统.设计系统主要在传统硬件的基础上,优化系统功能模块,其主要包括财务数据管理模块、网络管理模块等.在财务数据管理模块中,本次采用数据挖掘方法确定属性相似的财务数据,并借助Hadoop架构对电炉企业财务数据进行管理;在系统网络管理模块中,通过光纤/DDN传输中实现系统通信网络拓扑的搭建,并在TCP/IP等通信协议的支持下,完成网络管理模块的设计.通过优化各个功能模块,完成电炉企业财务数据分类管理系统设计,实现电炉企业财务数据分类管理功能.实验结果表明:所提系统响应速度快,CPU占有率低,分类管理准确度高于93%,用户反馈满意率高于80%,均优于对比方法,具有较大的应用价值.

Abstract

In order to improve the efficiency of financial data processing and improve the effect of financial data classification management,a financial data classification management system based on data mining is proposed and designed.This design system mainly on the basis of tra-ditional hardware,optimize the system function module,which mainly includes financial data management module,network management mod-ule and so on.In the financial data management module,the data mining method is used to determine the financial data with similar attributes,and the Hadoop architecture is used to manage the financial data of electric furnace enterprises.In the system network management module,the system communication network topology is built through optical fiber/DDN transmission,and the network management module is designed with the support of TCP/IP and other communication protocols.By optimizing each function module,the financial data classification manage-ment system of electric furnace enterprise is designed and the financial data classification management function of electric furnace enterprise is realized.The experimental results show that the proposed system has high response speed,low CPU occupancy,classification management accuracy higher than 93%,and user feedback satisfaction rate higher than 80%,all of which are superior to the comparison method and have great application value.

关键词

数据挖掘/人工智能/电炉企业财务数据/数据分类/管理系统

Key words

data mining/artificial intelligence/financial data of electric furnace enterprises/data classification/management system

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基金项目

四川省教育厅人文社会科学研究重点项目(SCYG2022-21)

出版年

2024
工业加热
西安电炉研究所有限公司

工业加热

CSTPCD
影响因子:0.257
ISSN:1002-1639
参考文献量16
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