服装制版系统参数量化模式识别

Pattern recognition of parameter quantization in garment board making system

针对传统服装制版系统参数量化模式识别方法的效率较低等问题,提出了一种基于小波分析的服装制版系统参数量化模式识别方法。提取服装制版系统中服装长度和围度等主要参数,借助概率密度函数确定服装制版系统参数的误差;通过主成分分析法计算系统参数信息的贡献率,获取服装制版系统参数高维度特征值,实现系统参数的降维处理;采用BP神经网络设计服装制版系统参数量化模式识别模型,使用小波分析方法对该模型求解,获取服装制版系统参数量化模式识别的最优解,实现了服装制版系统参数量化模式识别。结果表明,所提方法能够快速、准确地完成服装制版系统参数量化模式识别,具有较强的实用性。

In view of the low efficiency of traditional method of parameter quantification pattern recognition in garment board making system,this paper proposes a method of parameter quantification pattern recognition based on wavelet analysis.The main parameters of the system are extracted,including the length and circumference of the garment,and the error of the parameters of the garment board making system is determined by the probability density function.The contribution rate of the system parameter information is calculated by the principal component analysis method,and the high dimension characteristic value of the parameters of the garment board making system is obtained,and the dimension reduction of the principal component dimension of the system parameters is realized;BP neural network is used in the model of parameter quantification pattern recognition of garment board making system.The model is solved by wavelet analysis,and the optimal solution of the parameter quantification pattern recognition of the garment board making system is obtained,and the parameter quantification pattern recognition of the garment board making system can be realized.The simulation results show that the proposed method can quickly and accurately complete the parameter quantitative pattern recognition in garment board making system,and has a strongly practical performance.