On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network

Product market competitiveness is positively influenced by the aesthetic value of product form, which is closely related to product complexity. By measuring the cognitive complexity of the product, this research establishes the relationship between the complexity and aesthetics of the product using...

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Main Authors: Xinying Wu, Minggang Yang, Zishun Su, Xinxin Zhang
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/8407521
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author Xinying Wu
Minggang Yang
Zishun Su
Xinxin Zhang
author_facet Xinying Wu
Minggang Yang
Zishun Su
Xinxin Zhang
author_sort Xinying Wu
collection DOAJ
description Product market competitiveness is positively influenced by the aesthetic value of product form, which is closely related to product complexity. By measuring the cognitive complexity of the product, this research establishes the relationship between the complexity and aesthetics of the product using an artificial neural network. Hence the prediction of product beauty is achieved, which guides design decisions. In this article, the complexity of product form is first measured through a combination of hesitant-fuzzy theory and information axiom. Afterward, the result is weighted by exponential entropy and dimensionally compressed. This method makes data more suitable for the prediction with small samples, obtaining an accuracy improvement of up to 40% compared with traditional approaches. Finally, the importance order of the design elements which affect morphological complexity is acquired. Results show that three of the six complexity features (element number, object intelligence, and object detail) are more significant, impacting the aesthetic feeling of product form. The method increases the attractiveness of products to customers, providing valuable design support for enterprises and designers in the early days when a new product is designed, and reducing research and development risks.
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institution Kabale University
issn 1099-0526
language English
publishDate 2022-01-01
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record_format Article
series Complexity
spelling doaj-art-1807744a07304d5d91acb3460561820c2025-02-03T05:57:27ZengWileyComplexity1099-05262022-01-01202210.1155/2022/8407521On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural NetworkXinying Wu0Minggang Yang1Zishun Su2Xinxin Zhang3School of Art, Design and MediaSchool of Art, Design and MediaSchool of Art, Design and MediaSchool of Architecture and Art DesignProduct market competitiveness is positively influenced by the aesthetic value of product form, which is closely related to product complexity. By measuring the cognitive complexity of the product, this research establishes the relationship between the complexity and aesthetics of the product using an artificial neural network. Hence the prediction of product beauty is achieved, which guides design decisions. In this article, the complexity of product form is first measured through a combination of hesitant-fuzzy theory and information axiom. Afterward, the result is weighted by exponential entropy and dimensionally compressed. This method makes data more suitable for the prediction with small samples, obtaining an accuracy improvement of up to 40% compared with traditional approaches. Finally, the importance order of the design elements which affect morphological complexity is acquired. Results show that three of the six complexity features (element number, object intelligence, and object detail) are more significant, impacting the aesthetic feeling of product form. The method increases the attractiveness of products to customers, providing valuable design support for enterprises and designers in the early days when a new product is designed, and reducing research and development risks.http://dx.doi.org/10.1155/2022/8407521
spellingShingle Xinying Wu
Minggang Yang
Zishun Su
Xinxin Zhang
On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network
Complexity
title On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network
title_full On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network
title_fullStr On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network
title_full_unstemmed On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network
title_short On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network
title_sort on the prediction of product aesthetic evaluation based on hesitant fuzzy cognition and neural network
url http://dx.doi.org/10.1155/2022/8407521
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AT minggangyang onthepredictionofproductaestheticevaluationbasedonhesitantfuzzycognitionandneuralnetwork
AT zishunsu onthepredictionofproductaestheticevaluationbasedonhesitantfuzzycognitionandneuralnetwork
AT xinxinzhang onthepredictionofproductaestheticevaluationbasedonhesitantfuzzycognitionandneuralnetwork