Research on Students’ Mental Health Based on Data Mining Algorithms

With the diversification and rapid development of society, people’s living conditions, learning and friendship conditions, and employment conditions are facing increasing pressure, which greatly challenges people’s psychological endurance. Therefore, strengthening the mental health education of stud...

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Autor principal:	Mengjun Luo
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Medicine (General) R5-920 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/188b7e76eeaa46cf9e0eb8eeeffb58f9
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spelling	oai:doaj.org-article:188b7e76eeaa46cf9e0eb8eeeffb58f92021-11-08T02:36:39ZResearch on Students’ Mental Health Based on Data Mining Algorithms2040-230910.1155/2021/1382559https://doaj.org/article/188b7e76eeaa46cf9e0eb8eeeffb58f92021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1382559https://doaj.org/toc/2040-2309With the diversification and rapid development of society, people’s living conditions, learning and friendship conditions, and employment conditions are facing increasing pressure, which greatly challenges people’s psychological endurance. Therefore, strengthening the mental health education of students has become an urgent need of society and a hot issue of common concern. In order to solve the problems of high misjudgment rate and low work efficiency in the current mental health intelligence evaluation process, a mental health intelligence evaluation system based on a joint optimization algorithm is proposed. The joint optimization algorithm consists of an improved decision tree algorithm and an improved ANN algorithm. First, analyze the current research status of mental health intelligence evaluation, and construct the framework of mental health intelligence evaluation system; then collect mental health intelligence evaluation data based on data mining, use joint learning algorithm to analyze and classify mental health intelligence evaluation data, and obtain mental health intelligence evaluation results. Finally, through specific simulation experiments, the feasibility and superiority of the mental health intelligent evaluation system are analyzed. The results show that the system in the article overcomes the shortcomings of the existing mental health intelligence evaluation system, improves the accuracy of mental health intelligence evaluation, and improves the efficiency of mental health intelligence evaluation. It has good system stability and can meet the actual current situation, which are requirements for mental health intelligence evaluation.Mengjun LuoHindawi LimitedarticleMedicine (General)R5-920Medical technologyR855-855.5ENJournal of Healthcare Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920 Medical technology R855-855.5
spellingShingle	Medicine (General) R5-920 Medical technology R855-855.5 Mengjun Luo Research on Students’ Mental Health Based on Data Mining Algorithms
description	With the diversification and rapid development of society, people’s living conditions, learning and friendship conditions, and employment conditions are facing increasing pressure, which greatly challenges people’s psychological endurance. Therefore, strengthening the mental health education of students has become an urgent need of society and a hot issue of common concern. In order to solve the problems of high misjudgment rate and low work efficiency in the current mental health intelligence evaluation process, a mental health intelligence evaluation system based on a joint optimization algorithm is proposed. The joint optimization algorithm consists of an improved decision tree algorithm and an improved ANN algorithm. First, analyze the current research status of mental health intelligence evaluation, and construct the framework of mental health intelligence evaluation system; then collect mental health intelligence evaluation data based on data mining, use joint learning algorithm to analyze and classify mental health intelligence evaluation data, and obtain mental health intelligence evaluation results. Finally, through specific simulation experiments, the feasibility and superiority of the mental health intelligent evaluation system are analyzed. The results show that the system in the article overcomes the shortcomings of the existing mental health intelligence evaluation system, improves the accuracy of mental health intelligence evaluation, and improves the efficiency of mental health intelligence evaluation. It has good system stability and can meet the actual current situation, which are requirements for mental health intelligence evaluation.
format	article
author	Mengjun Luo
author_facet	Mengjun Luo
author_sort	Mengjun Luo
title	Research on Students’ Mental Health Based on Data Mining Algorithms
title_short	Research on Students’ Mental Health Based on Data Mining Algorithms
title_full	Research on Students’ Mental Health Based on Data Mining Algorithms
title_fullStr	Research on Students’ Mental Health Based on Data Mining Algorithms
title_full_unstemmed	Research on Students’ Mental Health Based on Data Mining Algorithms
title_sort	research on students’ mental health based on data mining algorithms
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/188b7e76eeaa46cf9e0eb8eeeffb58f9
work_keys_str_mv	AT mengjunluo researchonstudentsmentalhealthbasedondataminingalgorithms
_version_	1718443069515235328

Research on Students’ Mental Health Based on Data Mining Algorithms

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