参数寻优的企业会计数据智能提取与优化方法  

Intelligent Extraction and Optimization Method of Enterprise Accounting Data Based on Parameter Optimization

作　　者：吴永影 WU Yongying(School of Economics and Management,Fujian Vocational College of Agriculture,Fuzhou,Fujian 350000)

机构地区：[1]福建农业职业技术学院经济管理学院,福建福州350000

出　　处：《武夷学院学报》2025年第3期53-59,共7页Journal of Wuyi University

摘　　要：针对现有的数据提取方法不能简化成本数据分类属性集合,降低提取数据的置信度的问题,基于参数寻优算法,对企业会计数据智能提取与优化方法展开研究。确定企业会计各项参数,根据关联规则算法构建企业会计参数库,简化成本数据分类参数属性集合设计决策树配合遗传算法对参数寻优,寻找最优参数,在最优参数区间实现企业会计数据智能提取。通过对比实验验证了所提出的方法能够简化数据分类属性集合,提高成本数据属性信息增益概率,增加了提取成本数据的置信度,提取效果较好。The existing data extraction methods cannot simplify the set of cost data classification attributes,which reduces the confidence of the extracted data.This article conducts research on intelligent extraction and optimization methods for enterprise accounting data based on parameter optimization algorithms by determining various parameters of enterprise accounting,constructing an enterprise accounting parameter library based on association rule algorithms,simplifying the classification of cost data,designing a decision tree for parameter attribute sets,cooperating with genetic algorithms to optimize parameters,searching for the optimal parameters,and achieving intelligent extraction of enterprise accounting data within the optimal parameter range.Through comparative experiments,it was verified that the proposed method can simplify the set of data classification attributes,improve the probability of attribute information gain in cost data,increase the confidence level of extracting cost data,and achieve good extraction results.

关 键 词：企业会计数据 数据提取 参数寻优 数据挖掘 遗传算法 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]