摘要
为了提高企业创业期金融问题处理能力,提出基于Apriori关联算法的企业创业期金融数据采集方法。构建企业创业期金融数据的统计信息模型,重构企业创业期金融数据的高阶特征量,采用量化回归分析方法,分析企业创业期金融数据的定量递归。结合非线性比特序列重组方法进行企业创业期金融数据的离散融合处理,对金融数据进行Apriori关联规则挖掘,实现企业创业期金融数据的采集。仿真实验结果表明,采用该方法进行企业创业期金融数据采集的准确性较高,融合度水平较高,具有很好的企业创业期金融数据检测和特征分析能力。
In order to improve the ability to deal with financial problems in start-up period,a method of collecting enterprise start-up financial data based on Apriori correlation algorithm is proposed.This paper constructs the statistical information model of enterprise start-up financial data,reconstructs the high-order characteristic quantity of enterprise start-up financial data,and analyzes the quantitative recursion of enterprise start-up financial data by using quantitative regression analysis method.The discrete fusion processing of enterprise start-up financial data is carried out by combining the nonlinear bit sequence recombination method,and Apriori association rule mining is carried out to realize the collection of enterprise start-up financial data.The simulation results show that this method has a high accuracy and a high level of integration of enterprise start-up financial data collection,and has a good ability to detect and analyze enterprise start-up financial data.
作者
赖红清
LAI Hong-qing(School of Business Administration,Foshan Polytechnic College,Foshan Guangdong 528200,China)
出处
《长春工程学院学报（自然科学版）》
2019年第4期107-111,共5页
Journal of Changchun Institute of Technology：Natural Sciences Edition
基金
2018年佛山市哲社规划课题(2018-GJ071)。
