Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm

In order to improve the monitoring effect of financial security risk in colleges and universities, this paper studies the financial security risk control of colleges and universities combined with the big data clustering center scheduling algorithm and inverts the multilevel sampling algorithm of qu...

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Main Author: Chengjuan Xia
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2022/1361041
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author Chengjuan Xia
author_facet Chengjuan Xia
author_sort Chengjuan Xia
collection DOAJ
description In order to improve the monitoring effect of financial security risk in colleges and universities, this paper studies the financial security risk control of colleges and universities combined with the big data clustering center scheduling algorithm and inverts the multilevel sampling algorithm of quantum potential support. Moreover, this paper considers that the multilevel sampling algorithm is applied to the potential backscattering problem of the stationary Schrödinger equation to invert the support of the potential in the equation. In addition, this paper uses far-field data to invert the generalized linear sampling method of potential support and builds a college financial security risk monitoring model that relies on the big data clustering center scheduling algorithm. The experimental study shows that the financial security risk monitoring system for colleges and universities based on the big data clustering center scheduling algorithm proposed in this paper has good risk clustering and risk identification effects.
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spelling doaj-art-a1704fd161864e7a90d13ae87e95367b2025-08-20T02:20:41ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/1361041Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling AlgorithmChengjuan Xia0Finance DepartmentIn order to improve the monitoring effect of financial security risk in colleges and universities, this paper studies the financial security risk control of colleges and universities combined with the big data clustering center scheduling algorithm and inverts the multilevel sampling algorithm of quantum potential support. Moreover, this paper considers that the multilevel sampling algorithm is applied to the potential backscattering problem of the stationary Schrödinger equation to invert the support of the potential in the equation. In addition, this paper uses far-field data to invert the generalized linear sampling method of potential support and builds a college financial security risk monitoring model that relies on the big data clustering center scheduling algorithm. The experimental study shows that the financial security risk monitoring system for colleges and universities based on the big data clustering center scheduling algorithm proposed in this paper has good risk clustering and risk identification effects.http://dx.doi.org/10.1155/2022/1361041
spellingShingle Chengjuan Xia
Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm
Advances in Multimedia
title Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm
title_full Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm
title_fullStr Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm
title_full_unstemmed Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm
title_short Financial Security Risk Detection in Colleges and Universities Relying on Big Data Clustering Center Scheduling Algorithm
title_sort financial security risk detection in colleges and universities relying on big data clustering center scheduling algorithm
url http://dx.doi.org/10.1155/2022/1361041
work_keys_str_mv AT chengjuanxia financialsecurityriskdetectionincollegesanduniversitiesrelyingonbigdataclusteringcenterschedulingalgorithm