A multi-objective-driven product morphogen network model construction method

Abstract

The invention discloses a method for constructing a multi-objective-driven product morphological gene network model, which includes establishing a product case database and a target constraint information database, a feature sample set and a product morphological gene set, driving target and driving vocabulary extraction, and constructing a multi-objective image recognition system. Knowledge-driven space, establishment of target-driven morphological gene network, network topology analysis, etc., that is, to construct a multi-objective drive space based on user image cognitive experiments, analyze the design of product morphological gene nodes and edges, use product morphological genes as nodes, and Based on the correlation of each other as edges, a multi-objective-driven product form gene network model M-FGN is constructed, the network topology is analyzed, and implicit design knowledge is analyzed to assist designers and enterprises in product form design. The invention has the characteristics of being able to improve the subjectivity and ambiguity of user needs and the accuracy of conveying product images, and has good practicability.

Description

technical field [0001] The invention belongs to the field of product design, and in particular relates to a method for constructing a multi-objective-driven product morphological gene network model. Background technique [0002] Product image design has become an important design strategy for current enterprises. The subjectivity and ambiguity of user needs make it more and more difficult for companies and designers to grasp user needs. Designs that rely solely on computer-aided technology should actually have limited value. Therefore, how to effectively assist designers and enterprises to design products that better meet user needs and convey a unique brand image is an important issue facing product design. [0003] Product gene network (PGN) is a network form formed by applying complex network ideas to the concept of product gene. In recent years, some scholars have successively carried out research on the product gene network model. In the prior art, Liu Xiaojian et al....

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Problems solved by technology

However, there is still a lack of systematic exploration of complex network thinking in the mining of tacit knowledge contained in user perceptual imagery in product modeling design. Li Xuerui et al. constructed a gene network model of car side profile from the perspective of user perceptual image demand, but the selected image index is single. Ignoring the subjectivity and ambiguity of user needs in the product design process

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