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A Quantitative Method on Formative Elements Optimization of Car Styling Design

机译:汽车造型设计中形成要素优化的定量方法

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According to the basic principles of Kansei Engineering and BP neural network, the article establishes a non-linear relationship between the user’s perceptual evaluation and the car’s formative element. It also builds a strong anti-interference black box model, which may work out the precise value of the formative elements by the perceptual evaluations. The paper also discusses the model with deductive method, and the results show that the quantization and transformation in body design can be effectively solved by the method based on BP neural network and Kansei Engineering.
机译:根据Kansei Engineering和BP神经网络的基本原理,本文在用户的感知评估与汽车的构成要素之间建立了非线性关系。它还建立了一个强大的抗干扰黑匣子模型,可以通过感知评估得出形成元素的精确值。本文还对演绎模型进行了讨论,结果表明,基于BP神经网络和Kansei Engineering的方法可以有效地解决车身设计中的量化和变换问题。

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