摘要
目的实现产品配色设计的自动化。方法以感性工学为理论基础,采用神经网络为关键技术来研究产品配色。首先确定产品色彩的感性词汇与色彩设计要素,然后利用BP神经网络模型建立色彩编码与感性意象评价值之间的关系,最后结合豆浆机实例,设置BP模型中的输入层、输出层、隐含层的相关参数来进行豆浆机配色感性意象设计的实验仿真。结果测试验证了BP神经网络在产品配色设计中应用的有效性。结论表明了产品感性意象与产品配色之间的关系,论证了利用BP神经网络建立产品配色辅助设计系统的可行性。
It realizes the automation of product color matching design. It takes the kansei engineer as the theoretical foundation, uses the neural network as the key technology to study the product color-matched. The pairs of the kansei vocabulary of product color and color design elements are first determined, and then the BP neural network model is used to establish the relationship between the color encoding and the kansei image evaluation value. Finally, combined with the product of the soya bean milk machine, through setting parameters in the input layer, the output layer, and the hidden layer of the BP model, the kansei image of the product color design experiments are did with practical simulations. The validity of the model is verified by testing.The experimental result indicates the relationship between the kansei image and the color of the product clearly, and demonstrates the feasibility of constructing a system of product color-matched aided design on the bases of BP neural network.
出处
《包装工程》
CAS
CSCD
北大核心
2016年第10期136-141,共6页
Packaging Engineering
基金
陕西省科学技术研究发展计划项目(2015GY179)
陕西省科学技术研究发展计划项目(2014KE050049)
陕西省咸阳市科学技术研究计划项目(2014K03-14)
关键词
产品配色设计
感性工学
BP神经网络
product color-matched design
kansei engineer
BP neural network
