Paper Info
Title
Exploring The Financial Indicators To Improve The Pattern Recognition Of Economic Data Based On Machine Learning
Abstract
Various economic data in the financial market need to be pattern-recognized to improve the efficiency of economic data pattern recognition, further improve the accuracy of economic-related decisions, and promote stable economic development. Based on machine learning technology, this study establishes a statistical model by establishing a multiple regression model to extract financial indicators that have significant effects on the financing trade of listed companies. Moreover, this study provides a preliminary empirical model for judging whether a company conducts financing trade based on some company's financial indicators and uses data to verify the consistency of the model. In addition, this study conducts research and demonstration of the algorithm model of this research through empirical research. The research results show that the model shows high reliability and validity in accurately identifying whether the enterprise has the characteristics of conducting financing trade.
Year
DOI
Venue
2021
10.1007/s00521-020-05094-0
NEURAL COMPUTING & APPLICATIONS
Keywords
DocType
Volume
Machine learning, Economic data, Data mining, Pattern recognition
Journal
33
Issue
ISSN
Citations 
2
0941-0643
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Xiaohui Wei100.68
Wanling Chen200.34
Xiao Li3222.56