Intelligent Design Of Product Image Form Based On Cognitive Thinking

Product form is the expression of design ideas and the language and media of product features and conveys the meaning and symbolic of spiritual, cultural and other aspects. It is the interaction result of the objective factors of product function, structure, materials, technology and the designers’and users’subjective factors of aesthetic and value judgments. Based on this, the study analyzed the design issues related to the intelligent design of product image form and took the visual perception characteristics as a starting point to seek the method which can enhance the capability of the product image form intelligent design system and the design thinking quality evaluation method based on the law of cognition of users and designers. The main research contents and conclusions are as follows.(1) The study established the product image form factors identification model that is according to the simple regulating and identifiable discrimination of visual perception with quantification theory. Taking product form factors as independent variables and the emotional needs of users as dependent variable, the model was used to explore the relationship between users’Kansei image and product form factors with Kansei Engineering theory. And based on this, the individual factors and platform factors of product form to each Kansei image were identified. A computer aided analysis system of product image form factors was built. The analysis data was used in actual project and achieved good results.(2) According to the overall organization, constant memory, simple regulating and identifiable discrimination of visual perception, an improved4-layer BP neural network was established. Taking product form factors as input data, users’emotional needs as output data and the survey results of users’emotional needs as training samples, a product image intelligent evaluation system was built based on the improved4-layer BP neural network. A comparative study with the product image intelligent evaluation system that is based on conventional3-layer BP neural network was taken. And the results showed that the product form image intelligent evaluation systems based on the improved4-layer BP neural network is with high prediction accuracy.(3) Based on the analysis of design thinking process and the relationship unit of design process, design thinking mode and design strategy, a design thinking model was built with the generalized interactive genetic algorithm. An interactive intelligent design system of product multiple image form (IIDSPMIF) was established to simulate the multi-image-objective optimization in the design process. The experimental results show that IIDSPMIF system meets the design process generally and simulates the design strategy and design thinking mode well.(4) The study proposed a new design thinking quality evaluation method that translates the product design process into thinking network and quantifies thinking links with system sets and thinking coordinates to calculate the function values of design thinking quality. The method was used to analyze the differences of designers’ thinking quality to verify its feasibility. Finally, the method was used to analyze the thinking quality of designer C and the thinking quality of the generalized designer C-IIDSPMIF. The results showed that the IIDSPMIF system effectively enhances the creation degree, gathering degree, easy-smooth degree and other aspects of the generalized designer’s thinking quality.The research results obtained in this study is a beneficial exploration and attempt to the image form design of new product. In addition, the design thinking quality evaluation method provides a new practical and theoretical foundation for the study of design thinking.