Interactive Product Color Design Integrating Users' Cognitive Noise using Interactive Genetic Algorithms

Zhang Na; Yang Yanpu

doi:10.13433/j.cnki.1003-8728.20190066

Volume 38 Issue 5

May 2019

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Article Navigation > Mechanical Science and Technology for Aerospace Engineering > 2019 > 38(5): 698-703

Zhang Na, Yang Yanpu. Interactive Product Color Design Integrating Users' Cognitive Noise using Interactive Genetic Algorithms[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(5): 698-703. doi: 10.13433/j.cnki.1003-8728.20190066

Citation:

Zhang Na, Yang Yanpu. Interactive Product Color Design Integrating Users' Cognitive Noise using Interactive Genetic Algorithms[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(5): 698-703. doi: 10.13433/j.cnki.1003-8728.20190066

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Interactive Product Color Design Integrating Users' Cognitive Noise using Interactive Genetic Algorithms

doi: 10.13433/j.cnki.1003-8728.20190066

Zhang Na^1
,,
Yang Yanpu²

1.
Art College, Xi'an University of Science and Technology, Xi'an 710058, China
2.
School of Construction Machinery, Chang'an University, Xi'an 710064, China

Received Date: 2018-01-23
Publish Date: 2019-05-05

Abstract

Abstract

Product color design plays an important role in shaping product style and corporate identity. In order to effectively assist industrial designers in product color design process and accurately reflect users' image perception of product color schemes, the interactive genetic algorithm was used and combined with users' cognition degree and fatigue degree in product color evaluation process, and a users' cognition noise model was proposed. By computing the similarity among evaluation value and color value of product color schemes respectively, the related parameters of cognition noise model were figured out and used for fitness adjustment of product color schemes which are given by users. The process of interactive product color design was put forward by integrating users' cognitive noise and interactive genetic algorithms. Taking the color design of electric iron as an example and comparing with the ordinary interactive genetic algorithms. Simulation results show that:1) knowledge background difference will significantly affect users' cognition of product color; 2) the convergence of color design process increased by 37.5%, and the average evolutionary algebra decreased by 2.4 generations. These results indicate that the proposed method could help to improve the convergence and evolution efficiency of interactive product color design.
- product color design,
- interactive genetic algorithms,
- cognitive noise,
- color image

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References(13)

References

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