Research On Upholstered Furniture Evaluation System Based On Artificial Neural Network

Upholstered furniture evaluation is a complex and multi solution problem. Mult i objective evaluation research can effectively improve the design efficiency and qu ality of software furniture. In this paper, the development history of modern uphols ered furniture is divided into three stages:the formation of the period, the develop ment period, the exploration period. And analyzes the upholstered furniture develop ment status, for the current upholstered furniture industry in many aspects of the ad vantages and disadvantages, the analysis of the causes of the problems. According t o involved in the upholstered furniture design style, shape, function, decoration, stru cture, color, material and other factors, induction and analysis, provide a reference value for the investigation and collection of subsequent upholstered furniture design and pre evaluation questionnaire items.Through to the consumer psychological questionnaire survey using related analy sis, of upholstered furniture design preliminary evaluation were discussed, that the p roblem should be paid attention to in front of upholstered furniture design and the influence of the consumer to buy all kinds of characteristics, reduce the blindness a nd venture of the upholstered furniture design.Based on the principle of upholstered furniture is established according to the evaluation index, establish evaluation index for furniture design upholstered program. And the use of artificial neural network and hierarchical analysis method combinin g the comprehensive evaluation method, evaluation of upholstered furniture design s tage of inquiry, summed up a evaluation process for upholstered furniture design st age. Among them, the upholstered furniture indexes are layered with AHP method, obtained the index weight on the layer of index value and the lowest weight relativ e to the top value. Using AHP weight value can be obtained by the artificial neura 1 network model training data samples, so as to establish the model of artificial ne ural network upholstered furniture scheme design stage.