Analysis of interaction experience of sculpture product design based on perceptual machine model

Abstract

In this paper, the perceptual machine model is applied to analyze the interaction experience of sculpture product design to promote the innovative development of the cultural product design industry. In the design process, product information is passed layer by layer through a multilayer perceptual machine to adjust the magnitude of the weight vector values and obtain the optimal weight vector for sculpture product design. Using the perceptual machine training algorithm, the adjusted weights of the output layer network are calculated to clarify the value and status of perceptual factors in product design, thus proposing an interactive integration route for sculpture product design. A sculpture design product is used as an example to show the effect of the perceptual machine model on enhancing the interaction experience of the sculpture product design. The results show that the sculpture product is at level VI, the average weight of its frontal profile is e=0.46494, and the absolute value of the error between the modeling imagery result and the expected result is less than 0.1, which is within a reasonable error range. It can be seen that the perceptual machine model can transform the sculpture product design principles into user experience elements, which is conducive to the experiential development of sculpture product interaction design.

Keywords

• perceptron model
• sculpture product design
• training algorithm
• output layer network
• optimal weight vector
• 65d17