Lower garment waist dart parameter design method based on fuzzy logic and neural network

Abstract

The invention relates to a lower garment waist dart parameter design method based on fuzzy logic and a neural network. The method comprises the following steps: obtaining a lower garment waist dart parameter data set on the basis of the collection of human body lower part net body data, and creating a training data set and a test data set; constructing a hybrid intelligent model based on fuzzy logic and a neural network; training the hybrid intelligent model by using a training data set to obtain a trained hybrid intelligent model; analyzing main factors influencing the performance of the hybrid intelligent model, and determining optimal hybrid intelligent model structure parameters; and taking the waistline and the hipline of a user of the to-be-designed suits as the input of the hybrid intelligent model to obtain three pieces of template data of the front middle dart, the rear middle dart and the rear side dart, and designing the suits according to the obtained template data. According to the invention, the efficiency, the intelligence and the accuracy of the lower mounting plate are improved.

Description

technical field [0001] The invention relates to the technical field of garment structure design, in particular to a method for designing waist dart parameters of bottom garments based on fuzzy logic and neural network. Background technique [0002] The waist darts (or pleats) of bottoms (including skirts and trousers) originate from the circumference difference of the waist and hips of the human body, and are one of the important contents of the bottoms structure design. It is a key factor affecting the fit and comfort of the waist and hips of the human body. Experienced garment panel makers will set waist darts or pleat parameters in a targeted manner based on their years of practical experience and their judgment on the shape of the waist and hips of the human body, so as to obtain a bottoms model that meets the individual needs of consumers. And this is difficult for inexperienced novices to grasp accurately. With the rapid development of clothing online shopping, how t...

AI Technical Summary

Problems solved by technology

In the field of clothing structure design, some scholars have applied BP neural network and RBF neural network to the calculation of clothing model size, but no scholars have combined fuzzy logic and artificial neural network technology to design the parameters of the bottom model.

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