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Fuzzy Logic-Based Machine Learning Algorithm for Cultural and Creative Product Design.
1College of Fine Arts, Fujian Normal University, Fuzhou, Fujian 350117, China.
Computational Intelligence and Neuroscience
|June 20, 2022
Summary
This study introduces a novel interactive method for designing product color schemes using triangular fuzzy numbers. It helps designers create culturally relevant color palettes that align with user preferences and enhance product appeal.
Area of Science:
- Industrial Design
- Color Theory
- Computational Intelligence
Background:
- Industrial designers face challenges in creating color schemes for cultural products that resonate with user imagery preferences.
- Existing methods may not adequately integrate group user preferences or ensure aesthetic satisfaction.
Purpose of the Study:
- To propose an interactive color scheme design method for cultural and creative products.
- To effectively integrate group users' imagery preferences and satisfaction into the design process.
- To assist industrial designers in generating aesthetically pleasing and user-aligned color schemes.
Main Methods:
- Utilizing triangular fuzzy numbers for group consistency decision-making.
- Implementing an interactive genetic evolution algorithm for color scheme population.
- Calculating final color scheme selection based on color beauty metrics.
Main Results:
- The proposed method successfully integrates group users' imagery preferences.
- It facilitates the generation of color schemes that meet user satisfaction.
- Demonstrated effectiveness in multiuser decision consistency for color scheme design.
Conclusions:
- The interactive method enhances the design of color schemes for cultural and creative products.
- It provides a robust approach for incorporating diverse user preferences.
- Aids industrial designers in creating more appealing and contextually appropriate products.
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