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Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology
With the ever-changing internal and external environmental factors of enterprises, various uncertainties and risks faced by enterprises are increasing, and the feasibility of financial meltdown is increasing. Research on financial meltdown early warning can help enterprises to prevent the occurrence...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359837/ https://www.ncbi.nlm.nih.gov/pubmed/35958749 http://dx.doi.org/10.1155/2022/3319311 |
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author | Chen, Longxing Han, Ping |
author_facet | Chen, Longxing Han, Ping |
author_sort | Chen, Longxing |
collection | PubMed |
description | With the ever-changing internal and external environmental factors of enterprises, various uncertainties and risks faced by enterprises are increasing, and the feasibility of financial meltdown is increasing. Research on financial meltdown early warning can help enterprises to prevent the occurrence of peril in advance and take resultful measures to ensure the healthy development of enterprises. If a serious financial meltdown leads to the bankruptcy of enterprises, the financial meltdown is not sudden, but a gradual process. The occurrence of financial meltdown is not only a harbinger, but also predictable. Therefore, it is an urgent question to be solved for listed corporations in China that how to mine the message with early warning function from a large amount of financial data generated in the business process of enterprises. The continuous maturity of data mining technique just solves this question. Based on collaborative filtering technique, this paper analyzes the risk control optimization mold and algorithm of power grid corporations, which is of great signification. After research, this algorithm is 30% better than the traditional algorithm, and it is suitable to be proverbially used. |
format | Online Article Text |
id | pubmed-9359837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-93598372022-08-10 Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology Chen, Longxing Han, Ping Comput Intell Neurosci Research Article With the ever-changing internal and external environmental factors of enterprises, various uncertainties and risks faced by enterprises are increasing, and the feasibility of financial meltdown is increasing. Research on financial meltdown early warning can help enterprises to prevent the occurrence of peril in advance and take resultful measures to ensure the healthy development of enterprises. If a serious financial meltdown leads to the bankruptcy of enterprises, the financial meltdown is not sudden, but a gradual process. The occurrence of financial meltdown is not only a harbinger, but also predictable. Therefore, it is an urgent question to be solved for listed corporations in China that how to mine the message with early warning function from a large amount of financial data generated in the business process of enterprises. The continuous maturity of data mining technique just solves this question. Based on collaborative filtering technique, this paper analyzes the risk control optimization mold and algorithm of power grid corporations, which is of great signification. After research, this algorithm is 30% better than the traditional algorithm, and it is suitable to be proverbially used. Hindawi 2022-08-01 /pmc/articles/PMC9359837/ /pubmed/35958749 http://dx.doi.org/10.1155/2022/3319311 Text en Copyright © 2022 Longxing Chen and Ping Han. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chen, Longxing Han, Ping Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
title | Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
title_full | Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
title_fullStr | Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
title_full_unstemmed | Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
title_short | Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
title_sort | optimization mold and algorithm of risk control for power grid corporations based on collaborative filtering technology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359837/ https://www.ncbi.nlm.nih.gov/pubmed/35958749 http://dx.doi.org/10.1155/2022/3319311 |
work_keys_str_mv | AT chenlongxing optimizationmoldandalgorithmofriskcontrolforpowergridcorporationsbasedoncollaborativefilteringtechnology AT hanping optimizationmoldandalgorithmofriskcontrolforpowergridcorporationsbasedoncollaborativefilteringtechnology |