Exploration of Cultural and Creative Product Design Thinking in the Age of Artificial Intelligence

IF 3.1 Q1 Mathematics
Shanlin Zhang
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引用次数: 0

Abstract

In this paper, we use the inference rules and reasoning rules in the shape grammar to extract the elements of the cultural and creative product design, obtain the graphical elements of the cultural and creative product, import the determined graphical elements of the cultural and creative product of the inference object into Illustrator, use the pen tool to outline the morphological curves of the ornaments into paths, and at the same time organize the outlined morphological curves into the gallery. Aiming at the problem that it is difficult to obtain the optimal cultural and creative product design works in the cultural and creative product design based on shape grammar and using genetic algorithm to optimize the cultural and creative product design model. The optimization model of cultural and creative product design is empirically analyzed using simulation analysis based on research data and parameter settings. The results show that the scaling values (tx d 1, tx d 2) of the first layer in the optimal design parameters of the cultural and creative products are approximated to be the maximum value, and the optimal solutions in the samples are (3.61, 0.437) and (3.61, 0.268), respectively, which confirms that the optimization model of the cultural and creative product design can provide theoretical knowledge and reference value for the research of the cultural and creative product design.
人工智能时代的文化创意产品设计思维探索
本文利用形状语法中的推理规则和推理规则提取文创产品设计元素,得到文创产品的图形元素,将推理对象确定的文创产品图形元素导入Illustrator中,用钢笔工具将装饰物的形态曲线勾勒成路径,同时将勾勒出的形态曲线整理成图库。针对基于形态语法的文化创意产品设计中难以获得最优文化创意产品设计作品的问题,利用遗传算法对文化创意产品设计模型进行优化。根据研究数据和参数设置,采用仿真分析方法对文化创意产品设计优化模型进行了实证分析。结果表明,文创产品优化设计参数中第一层的缩放值(tx d 1,tx d 2)近似为最大值,样本中的最优解分别为(3.61,0.437)和(3.61,0.268),证实了文创产品设计优化模型可以为文创产品设计研究提供理论知识和参考价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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