Research On Product Form Design For Extension Reasoning And Artificial Neural Network

The change of social demand leads to the diversified development of product value.Under the trend of user-oriented design,people’s emotional demand for products is increasingly strong.In order to satisfy users’ multi-dimensional emotional needs for products,this paper integrated extension reasoning method and artificial neural network algorithm to carry out research on product form,effective extension reasoning on product design knowledge,and then build product form emotional prediction model.Take the center console of engineering vehicle as an example to explore the relationship between product shape,color and material and its influence on user emotion.Firstly,the extension reasoning system of target product is constructed,the knowledge of product form design is obtained and the primitive model is established.Using the extension reasoning method to carry on the system extension analysis and transformation of product form primitive model,complete the qualitative analysis of product form.Secondly,product form samples and user emotion evaluation space are established under the extension reasoning system.The dominant feature factors of product form characteristics and user emotion evaluation words are extracted and characterized by quantitative research methods such as cluster analysis,factor analysis and semantic difference method,so as to determine the threshold interval of the target product with respect to the feature.Thirdly,the artificial neural network model is designed and the code is written.The product form emotion prediction model is constructed by taking the product form feature code as input data and the product form user emotion evaluation as output data.The model is trained,tested and evaluated,and the product form design method integrating extension reasoning and artificial neural network is integrated.Finally,the traditional multiple linear regression prediction model was constructed to compare and analyze the effectiveness and accuracy of the product form emotion prediction model,so as to guide the generation of engineering vehicle center console product design scheme and verify the feasibility of the integration method.In this paper,a product form design method integrating extension reasoning and artificial neural network is proposed.Based on effective extension reasoning and formal description of product form,artificial neural network algorithm is used to construct product form emotion prediction model.By comparing and evaluating the performance,accuracy and prediction ability of the prediction model,the advantages of the integrated method in the prediction of product form emotion were verified,and the cross-fusion and complementarity of the theoretical methods were tried and explored.