通过结合灰色关系分析和粒子群优化来研究陶酒瓶的参数设计,支持向量回归
Wei Guo1, Xing Lu2, Zhenwei Zhang3
1College of Arts, Kyungpook National University, Daegu Metropolitan, 41566, South Korea.
Scientific reports
|November 7, 2025
概括
这项研究介绍了文化产品的智能设计方法,使用Kansei工程,灰色关系分析 (GRA) 和粒子群优化支持向量回归 (PSO-SVR). 它确保产品与用户的情绪保持一致,增强市场竞争力.
科学领域:
- 工业设计 工业设计 工业设计
- 人与计算机的交互
- 计算智能是一种计算智能.
背景情况:
- 传统的文化产品设计在很大程度上依赖于主观的设计师美学,往往不符合消费者的期望.
- 设计师和消费者之间的认知差异可能导致市场拒绝创意产品.
研究的目的:
- 为文化产品开发一种智能,参数设计方法,与用户的情感意图保持一致.
- 准确量化用户的情感需求,并将其转化为产品设计参数.
主要方法:
- 利用网络抓取和专家采访来收集用户的情绪数据和产品样本.
- 采用灰色关系分析 (GRA) 来确定情感需求的最佳权重,并确定关键需求.
- 集成粒子群优化-支持向量回归 (PSO-SVR) 来建模情感需求和产品形态之间的关系.
主要成果:
- 确定"坚强"",时尚"和"精致"作为陶酒瓶的关键情感需求.
- PSO-SVR映射模型准确地预测了设计参数的优化.
- 优化的设计方案显示了与模型预测的高度匹配,验证了该方法的可行性.
结论:
- 提出的基于Kansei工程的参数设计方法有效地弥合了设计师主观性和消费者需求之间的差距.
- 这种方法有助于准确预测用户的情绪,减少产品开发风险,提高文化和创意企业的市场竞争力.
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