Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)

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Financial Crisis Prediction Based on GWO-SVM

Sampling from the Chinese Environmental Protection Industry

Authors
Jian Ke1, Shiqian Yu1, *
1Newhuadu Business School, Minjiang University, Fuzhou, 350100, Fujian, China
*Corresponding author. Email: yushiqian_2022mba@nbs.edu.cn
Corresponding Author
Shiqian Yu
Available Online 28 August 2023.
DOI
10.2991/978-94-6463-222-4_58How to use a DOI?
Keywords
GWO-SVM; Machine Learning; Financial Crisis Prediction; The Grey Wolf Optimization Algorithm
Abstract

Financial Crisis Prediction (FCP) is an important initiative to prevent the outbreak of financial crisis in enterprises, which is significant to the safe operation and economic stability of enterprises. To improve the prediction accuracy of the occurrence of corporate financial crisis, a financial crisis prediction model based on the optimized support vector machine of the Grey Wolf Optimization Algorithm is proposed. This paper firstly introduces the basic principles of SVM and GWO; then proposes the SVM model based on the penalty parameters C and g optimization; and finally compares the prediction performance of the environmental protection industry by different machine learning methods, taking them as examples. The results show that GWO- SVM can more accurately predict the likelihood of corporate crises. As can be seen the model has high application prospects.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
28 August 2023
ISBN
978-94-6463-222-4
ISSN
2589-4919
DOI
10.2991/978-94-6463-222-4_58How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jian Ke
AU  - Shiqian Yu
PY  - 2023
DA  - 2023/08/28
TI  - Financial Crisis Prediction Based on GWO-SVM
BT  - Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
PB  - Atlantis Press
SP  - 535
EP  - 543
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-222-4_58
DO  - 10.2991/978-94-6463-222-4_58
ID  - Ke2023
ER  -