Fuzzy Relationship between Kansei Images: A Grey Decision-Making Method for Product Form Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.3390/app14135728
Current design decision-making methods ignore the fuzzy relationship between Kansei images, and the use of constant weights reduces the accuracy of cognitive evaluation results. To solve these problems, this paper proposes a grey decision-making method for product form driven by the fuzzy relationship between Kansei images. First, according to the initial weight of the Kansei images, variable weight theory is used to determine the Kansei image variable weights of the samples, and the variable weight comprehensive evaluation results for each sample are obtained. Then, based on the correlation and angle of the Kansei images, a cobweb diagram is drawn to represent the fuzzy relationship between the Kansei images of each sample. Combined with the cobweb grey target decision-making model (CGTDM) for multiple Kansei images, decision coefficients are calculated. The decision coefficients are compared and ranked to determine the relatively optimal design reference sample. Finally, the constructed model is compared with the CGTDM for multiple Kansei images and TOPSIS. The results show that the difference coefficient of the proposed method is the largest, and it can reflect the decision-making thinking of the designers and improve the discrimination among the decision-making results to a certain extent.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app14135728
- https://www.mdpi.com/2076-3417/14/13/5728/pdf?version=1720403018
- OA Status
- gold
- Cited By
- 1
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400237533
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400237533Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/app14135728Digital Object Identifier
- Title
-
Fuzzy Relationship between Kansei Images: A Grey Decision-Making Method for Product FormWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-30Full publication date if available
- Authors
-
Shijie Wang, Shutao Zhang, Jianning Su, Zhiqiang Yang, Shifeng Liu, Aimin Zhou, Wenjin Yang, Kai QiuList of authors in order
- Landing page
-
https://doi.org/10.3390/app14135728Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/14/13/5728/pdf?version=1720403018Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2076-3417/14/13/5728/pdf?version=1720403018Direct OA link when available
- Concepts
-
Kansei, Kansei engineering, Mathematics, Fuzzy logic, Sample (material), Artificial intelligence, TOPSIS, Relation (database), Data mining, Product (mathematics), Pattern recognition (psychology), Computer science, Statistics, Operations research, Human–computer interaction, Chemistry, Geometry, ChromatographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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