Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching

With the continuous application of the art industry in various fields, more and more people choose to systematically learn the knowledge of the art industry. In the art major, image painting is one of the important contents of the art major. How to improve students’ aesthetic quality and comprehensi...

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Autores principales:	Weiming Xing, Jian Zhang, Quan Zou, Jun Lin
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/13ca1430ff8f47e3aa1a428fca5aaa0b
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spelling	oai:doaj.org-article:13ca1430ff8f47e3aa1a428fca5aaa0b2021-11-29T00:55:40ZApplication of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching1687-527310.1155/2021/3302617https://doaj.org/article/13ca1430ff8f47e3aa1a428fca5aaa0b2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3302617https://doaj.org/toc/1687-5273With the continuous application of the art industry in various fields, more and more people choose to systematically learn the knowledge of the art industry. In the art major, image painting is one of the important contents of the art major. How to improve students’ aesthetic quality and comprehensive professional quality is studied, in which the content learning of image painting art is the key. Therefore, we have carried out technical exploration and result analysis based on Gaussian mutation genetic algorithm to optimize the application of neural network in image painting art teaching. We use Gaussian mutation genetic algorithm to study the neural network optimized teaching cloud platform technology. Compared with the traditional algorithm, the algorithm proposed in this paper has more funny computational efficiency, being able to comprehensively evaluate and improve students’ aesthetic quality and comprehensive professional quality. Gaussian mutation genetic algorithm can effectively improve the knowledge search ability of the platform and the running speed of the teaching platform. In the future research in the field of art industry, neural network will optimize the teaching cloud platform technology, which has laid a solid foundation for improving students’ aesthetic quality and comprehensive professional quality.Weiming XingJian ZhangQuan ZouJun LinHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENComputational Intelligence and Neuroscience, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Weiming Xing Jian Zhang Quan Zou Jun Lin Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching
description	With the continuous application of the art industry in various fields, more and more people choose to systematically learn the knowledge of the art industry. In the art major, image painting is one of the important contents of the art major. How to improve students’ aesthetic quality and comprehensive professional quality is studied, in which the content learning of image painting art is the key. Therefore, we have carried out technical exploration and result analysis based on Gaussian mutation genetic algorithm to optimize the application of neural network in image painting art teaching. We use Gaussian mutation genetic algorithm to study the neural network optimized teaching cloud platform technology. Compared with the traditional algorithm, the algorithm proposed in this paper has more funny computational efficiency, being able to comprehensively evaluate and improve students’ aesthetic quality and comprehensive professional quality. Gaussian mutation genetic algorithm can effectively improve the knowledge search ability of the platform and the running speed of the teaching platform. In the future research in the field of art industry, neural network will optimize the teaching cloud platform technology, which has laid a solid foundation for improving students’ aesthetic quality and comprehensive professional quality.
format	article
author	Weiming Xing Jian Zhang Quan Zou Jun Lin
author_facet	Weiming Xing Jian Zhang Quan Zou Jun Lin
author_sort	Weiming Xing
title	Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching
title_short	Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching
title_full	Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching
title_fullStr	Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching
title_full_unstemmed	Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching
title_sort	application of gauss mutation genetic algorithm to optimize neural network in image painting art teaching
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/13ca1430ff8f47e3aa1a428fca5aaa0b
work_keys_str_mv	AT weimingxing applicationofgaussmutationgeneticalgorithmtooptimizeneuralnetworkinimagepaintingartteaching AT jianzhang applicationofgaussmutationgeneticalgorithmtooptimizeneuralnetworkinimagepaintingartteaching AT quanzou applicationofgaussmutationgeneticalgorithmtooptimizeneuralnetworkinimagepaintingartteaching AT junlin applicationofgaussmutationgeneticalgorithmtooptimizeneuralnetworkinimagepaintingartteaching
_version_	1718407754118332416

Application of Gauss Mutation Genetic Algorithm to Optimize Neural Network in Image Painting Art Teaching

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