Financial crisis early warning system of Listed Enterprises Based on particle swarm optimization algorithm

被引：0

作者：

Tong Y. ^{[1
]}

机构：

[1] Yonyou Seentao School of Accounting, Shaanxi Technical College of Finance & Economics, Xianyang

来源：

Journal of Commercial Biotechnology | 2022年 / 27卷 / 01期

关键词：

Crisis warning; Financial crisis; Listed enterprises; particle swarm optimization algorithm;

D O I：

10.5912/jcb1054

中图分类号：

学科分类号：

摘要：

Enterprise financial crisis early warning system can help enterprises find and avoid potential financial risks in time, which is widely used in enterprise financial management. The actual use efficiency directly affects the development of enterprises. In this article, the purpose of the enterprise financial crisis early warning system is examined, along with any present issues with it. The paper also suggests some improvements that may be made to the company’s financial crisis early warning system. The overall research study founded that the financial crisis shows a significant effect on listed enterprises based on the all-particle optimization algorithm. © 2022 ThinkBiotech LLC. All rights reserved.

引用

页码：86 / 97

页数：11

共 20 条

[1]

Abotaleb I.S., Et al., Causes, early warning signs, and impacts of out-of-sequence construction: Expert-based survey analysis, Journal of Management in Engineering, 35, 6, (2019)

[2]

Bury T.M., Bauch C.T., Anand M., Detecting and distinguishing tipping points using spectral early warning signals, Journal of the Royal Society Interface, 17, 170, (2020)

[3]

Conti A., Et al., Venture capital investment strategies under financing constraints: Evidence from the 2008 financial crisis, Research Policy, 48, 3, pp. 799-812, (2019)

[4]

Cotugno M., Galletta S., Mazzu S., Shareholder value in European banks after the global financial crisis: an empirical analysis, International Journal of Applied Decision Sciences, 14, 5, pp. 477-497, (2021)

[5]

de Figueiredo R.J., Feldman E.R., Rawley E., The costs of refocusing: Evidence from hedge fund closures during the financial crisis, Strategic Management Journal, 40, 8, pp. 1268-1290, (2019)

[6]

Deng Z., Yan M., Xiao X., An early risk warning of cross-border e-commerce using BP neural network, Mobile Information Systems, 2021, (2021)

[7]

Dian S., Et al., Integrating wildfires propagation prediction into early warning of electrical transmission line outages, IEEE Access, 7, pp. 27586-27603, (2019)

[8]

Hu J., Construction of Financial Risk Early Warning Model Based on Ant Colony Algorithm, International Conference on Multi-modal Information Analytics, (2022)

[9]

Ismail M.S., Hussain S.I., Noorani M.S.M., Detecting early warning signals of major financial crashes in bitcoin using persistent homology, IEEE Access, 8, pp. 202042-202057, (2020)

[10]

Joo K., Et al., Impact of the global financial crisis on the crude oil market, Energy Strategy Reviews, 30, (2020)

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