Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm

Abstract Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yuan Xin, Bu Henan, Niu Jianmin, Yu Wenjuan, Zhou Honggen, Ji Xingyu, Ye Pengfei
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/75711caf81a24e698d367f032ffefbc6
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:75711caf81a24e698d367f032ffefbc6
record_format	dspace
spelling	oai:doaj.org-article:75711caf81a24e698d367f032ffefbc62021-12-02T16:14:56ZCoating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm10.1038/s41598-021-93628-42045-2322https://doaj.org/article/75711caf81a24e698d367f032ffefbc62021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93628-4https://doaj.org/toc/2045-2322Abstract Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is < 1.02 and the mean absolute error is < 0.75, the prediction accuracy is significantly better than other research methods, which proves the effectiveness of the method.Yuan XinBu HenanNiu JianminYu WenjuanZhou HonggenJi XingyuYe PengfeiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yuan Xin Bu Henan Niu Jianmin Yu Wenjuan Zhou Honggen Ji Xingyu Ye Pengfei Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
description	Abstract Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is < 1.02 and the mean absolute error is < 0.75, the prediction accuracy is significantly better than other research methods, which proves the effectiveness of the method.
format	article
author	Yuan Xin Bu Henan Niu Jianmin Yu Wenjuan Zhou Honggen Ji Xingyu Ye Pengfei
author_facet	Yuan Xin Bu Henan Niu Jianmin Yu Wenjuan Zhou Honggen Ji Xingyu Ye Pengfei
author_sort	Yuan Xin
title	Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
title_short	Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
title_full	Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
title_fullStr	Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
title_full_unstemmed	Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
title_sort	coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/75711caf81a24e698d367f032ffefbc6
work_keys_str_mv	AT yuanxin coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm AT buhenan coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm AT niujianmin coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm AT yuwenjuan coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm AT zhouhonggen coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm AT jixingyu coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm AT yepengfei coatingmatchingrecommendationbasedonimprovedfuzzycomprehensiveevaluationandcollaborativefilteringalgorithm
_version_	1718384297919905792

Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm

Ejemplares similares