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...
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| Veröffentlicht in: | Computational intelligence and neuroscience 2022-08, Vol.2022, p.1-9 |
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| creator | Chen, Longxing Han, Ping |
| 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. |
| doi_str_mv | 10.1155/2022/3319311 |
| format | Article |
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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.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2022/3319311</identifier><identifier>PMID: 35958749</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Algorithms ; Bankruptcy ; Bankruptcy laws ; Clustering ; Collaboration ; Consumers ; Data mining ; Environmental factors ; Filtration ; Investments ; Molds ; Neural networks ; Optimization ; Questions ; Risk analysis ; Risk management ; Securities markets ; Stock exchanges</subject><ispartof>Computational intelligence and neuroscience, 2022-08, Vol.2022, p.1-9</ispartof><rights>Copyright © 2022 Longxing Chen and Ping Han.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Longxing Chen and Ping Han. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Longxing Chen and Ping Han. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c340t-8ee87faca996569376295a05e0623957faea7a5510db36857fe0fbb512afad4a3</cites><orcidid>0000-0001-7592-5815</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359837/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359837/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,886,27926,27927,53793,53795</link.rule.ids></links><search><contributor>Ding, Baiyuan</contributor><contributor>Baiyuan Ding</contributor><creatorcontrib>Chen, Longxing</creatorcontrib><creatorcontrib>Han, Ping</creatorcontrib><title>Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology</title><title>Computational intelligence and neuroscience</title><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.</description><subject>Algorithms</subject><subject>Bankruptcy</subject><subject>Bankruptcy laws</subject><subject>Clustering</subject><subject>Collaboration</subject><subject>Consumers</subject><subject>Data mining</subject><subject>Environmental factors</subject><subject>Filtration</subject><subject>Investments</subject><subject>Molds</subject><subject>Neural networks</subject><subject>Optimization</subject><subject>Questions</subject><subject>Risk analysis</subject><subject>Risk management</subject><subject>Securities markets</subject><subject>Stock 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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. 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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; Wiley Online Library (Open Access Collection); PubMed Central; Alma/SFX Local Collection |
| subjects | Algorithms Bankruptcy Bankruptcy laws Clustering Collaboration Consumers Data mining Environmental factors Filtration Investments Molds Neural networks Optimization Questions Risk analysis Risk management Securities markets Stock exchanges |
| title | Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering Technology |
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