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Fusion of Cognitive Information: Evaluation and Evolution Method of Product Image Form

机译:认知信息融合:产品图像形式的评估和演化方法

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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.
机译:为了实现一系列产品的开发过程中图像特征的稳定性和遗传,我们全面分析了用户,设计师和工程师之间的认知差异,并提出了一种基于的产品形式的智能设计方法的多标语决策系统Logistic回归模型,相对熵理论和偏好映射(Prefermap)。首先,从设计对象的角色特征的角度来看,使用逻辑回归模型和相对熵理论构建平衡评估模型。其次,组合多维感知空间和产品形式的特性测量,基于prefermap构建图像形式的适应性功能。第三,应用了遗传算法来建立智能图像风格的设计方法,可以通过创新设计引导产品系列的图像形式开发。最后,通过拍摄奥迪A4L系列前灯作为示例来验证该方法。两个新方案的图像评估大于前七代大灯的图像评估。结果验证了该方法的有效性和可行性。在本文中,我们构成了一个相对初步的模型来解释认知信息的融合。需要进一步研究更多主观和客观因素,算法和图像识别技术,以改善我们未来的工作中的模型。

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