基于改进BP神经网络的的西服肩袖造型研究

 袖窿与袖子是服装结构中最复杂的部位之一，该部位的结构直接影响服装的肩袖造型和着装舒适性。本文把改进BP人工神经网络算法用于西服肩袖的造型设计, 实现了西服样板中袖与袖窿结构到成衣肩袖造型的自动映射, 并用30个样本对神经网络进行训练，10个样本进行测试，测试结果验证了该方法的有效性和精确性，对西服肩袖部位的造型具有预知性，减少袖疵病的发生，提高制板效率。

Study on rotator cuff of suit based on improved BP neural network

Armhole and sleeve is one of the most complicated parts in the garment pattern, and the pattern of this part can directly affect the model of the rotator cuff and the thermal comfort. This paper adopts the algorithm in improved BP artificial neural network to design the rotator cuff of the suit, approches the automatic mapping relation which is from the matching specifications sizes of sleeve and armholestructure to rotator cuff style of clothing. 30 samples were used to train BP neural network and 10 samples were measured, which show that this method is effective and accurate, and can predict the rotator cuff style of suit , reduce the defects of sleeve and improve the efficiency of the pattern design.