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

Author:

Yubo Cao1

Affiliation:

1. Business College of Shanxi University, Taiyuan, Shanxi, China

Abstract

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.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference24 articles.

1. Congestion management, enhancing transient stability of power systems;Esmaili;Appl Energy,2010

2. Stocastic multi-Multi-objective congestion management in power markets improving voltage and transient stabilities;Esmaili;Eur Trans Electr Power,2010

3. Multi-objective congestion management by modified augumented e-contraint method;Esmaili;Appl Energy,2011

4. Transient Stability limit conditions analysis using a corrected transient energy function approach;Fang;IEEE Trans Power Syst,2000

5. Congestion management using multi objective p swarm optimization;Hazra;IEEE Trans Power Syst,2007

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Computational Intelligence in Business Management: Strategies for Innovation and Optimization;2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA);2024-05-23

2. Proactive decision making by incorporation of discrete random sums;Intelligent Decision Technologies;2023-11-20

3. Problems and Countermeasures of Enterprise Financial Sharing in the Context of Big Data;Applied Mathematics and Nonlinear Sciences;2023-10-15

4. The state of development of artificial intelligence in polish industry: opinions of employees;International Journal of Contemporary Management;2022-12-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3