基于优化RBF神经网络的丝织物缝纫性能客观评价  

Objective Evaluaion of Silk Fabric Sewability Based on Optimize RBF Neural Network

作　　者：吴懋刚[1] 潘永惠[1] 范蕤[1] 

机构地区：[1]江阴职业技术学院计算机科学系,江苏无锡214405

出　　处：《淮阴师范学院学报（自然科学版）》2010年第4期326-329,共4页Journal of Huaiyin Teachers College;Natural Science Edition

摘　　要：提出了一种基于优化RBF神经网络的丝织物缝纫性能客观评价系统.该系统根据丝织物面料的FAST力学指标与缝纫性能之间的关系,运用神经网络的方法进行面料缝纫性能评价和预测,并提出了一种基于模糊核聚类的优化径向基神经网络学习算法.实验表明,该系统对一般丝型织物的缝纫平整性能评价预测具有客观、快速和高效等优点.According to the relations between FAST mechanical properties and silk fabric sewability,we proposed an optimized objective evaluation system of silk fabric sewability based on Fuzzy kernel clustering and RBF neural network.Our experimental results demonstrate that the proposed system could efficiently be used as an objective sewability prediction system with high accuracy.

关 键 词：FAST系统 缝纫平整度 模糊核聚类 RBF神经网络 客观评价 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]