Innovation of enterprise financial management based on machine learning and artificial intelligence technology

被引:3
作者
Cao Yubo [1 ]
机构
[1] Shanxi Univ, Business Coll, Taiyuan, Shanxi, Peoples R China
关键词
Machine learning; artificial intelligence; financial management; innovation optimization; PARTICLE SWARM OPTIMIZATION; CONGESTION MANAGEMENT; TRANSIENT STABILITY;
D O I
10.3233/JIFS-189510
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the development of economic globalization, the competition between companies is increasing and becoming a norm. As one of the main value-added tools, financial management has greatly improved its position in business management. Traditional financial management is difficult to keep up with the pace of modern company management, which to a large extent hinders the effective development of enterprises. Therefore, under the current macroeconomic background, the necessity of studying financial management innovation has become more urgent. In this context, seeking innovation is not only a problem for enterprises, but also an important strategic goal of economic development and the concept of national modern enterprise development. Many studies have been carried out in the field of technological innovation, and few have focused on innovation in financial management. Exploratory research on the factors that affect the choice of financial management mode and route planning is important both in reality and in theory. It can help enterprises to gain greater competitive advantage through innovative financial management and improve their operating efficiency and production quality. This paper is based on learning. A research on the innovation of enterprise financial management is carried out on machine and artificial intelligence technology.
引用
收藏
页码:6767 / 6778
页数:12
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