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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-93628-4 |
| _version_ | 1818999114865573888 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-20T22:12:17Z |
| format | Article |
| id | doaj.art-75711caf81a24e698d367f032ffefbc6 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-20T22:12:17Z |
| publishDate | 2021-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-75711caf81a24e698d367f032ffefbc62022-12-21T19:25:08ZengNature PortfolioScientific Reports2045-23222021-07-0111111410.1038/s41598-021-93628-4Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithmYuan Xin0Bu Henan1Niu Jianmin2Yu Wenjuan3Zhou Honggen4Ji Xingyu5Ye Pengfei6School of Mechanical Engineering, Jiangsu University of Science and TechnologySchool of Mechanical Engineering, Jiangsu University of Science and TechnologyShanghai Shipbuilding Technology Research InstituteShanghai Shipbuilding Technology Research InstituteSchool of Mechanical Engineering, Jiangsu University of Science and TechnologySchool of Mechanical Engineering, Jiangsu University of Science and TechnologySchool of Mechanical Engineering, Jiangsu University of Science and TechnologyAbstract 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.https://doi.org/10.1038/s41598-021-93628-4 |
| spellingShingle | 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 Scientific Reports |
| title | 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_short | 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 |
| url | https://doi.org/10.1038/s41598-021-93628-4 |
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