In order to realize the stability and inheritance of image characteristics in the development process of a series of products, we comprehensively analyzed the cognitive differences among users, designers, and engineers and propose a multicriteria decision system for an intelligent design method of product forms based on a logistic regression model, relative entropy theory, and preference mapping (PREFMAP). First, from the perspective of the role characteristics of the design subjects, an equilibrium evaluation model was constructed using the logistic regression model and relative entropy theory. Second, combining the multidimensional perception space and the characteristics measurement of the product form, the fitness function of the image form was constructed based on PREFMAP. Third, a genetic algorithm was applied to establish the intelligent image-style-oriented design method, which could guide the image form development of a product series through innovative design. Lastly, the method was verified by taking Audi A4L series headlights as an example. And the image evaluation of the two new schemes was greater than that of the previous seven generations of headlights. The results verify the effectiveness and feasibility of the method. In this paper, we structured a relatively preliminary model to explain the fusion of cognitive information. More subjective and objective factors, algorithms, and image recognition technology need to be further studied to improve the model in our future work.

中文翻译：

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认知信息融合：产品形象形态评价与演化方法


为了实现系列产品开发过程中形象特征的稳定和传承，综合分析了用户、设计师、工程师的认知差异，提出了基于多准则决策的产品形态智能设计方法。逻辑回归模型、相对熵理论和偏好映射 (PREFMAP)。首先，从设计主体的角色特征角度出发，运用逻辑回归模型和相对熵理论构建均衡评价模型。其次，结合多维感知空间和产品形态特征测度，基于PREFMAP构建图像形态适应度函数。第三，应用遗传算法建立面向形象风格的智能设计方法，通过创新设计指导产品系列的形象发展。最后以奥迪A4L系列车头灯为例对该方法进行了验证。并且两款新方案的形象评价均大于前七代大灯。结果验证了该方法的有效性和可行性。在本文中，我们构建了一个相对初步的模型来解释认知信息的融合。更多的主客观因素、算法和图像识别技术需要进一步研究，以在今后的工作中改进模型。