In order to more accurately and efficiently match cotton,a novel computer automatic cotton blending prediction mathematical model method is proposed.The method firstly filters and extends the spinning data,establishing a mapping relationship matrix,then we use the cascade prediction model to solve the nonlinear relationship between spinning quality and raw cotton performance.Finally,linear differential method and nonlinear differential iterative method are used to correct the input and output for many times,so as to reduce the systematic deviation of the model and achieve accurate prediction and efficient cotton distribution.Compared with other existing methods,this method is applied to a textile industry.After investigation,the production cost is reduced by 15% and the benefit is increased by 25%.This article provides technical support for companies that want to reduce costs and increase efficiency.
类型: 国际会议
作者: QingE Wu,Changsheng Fan,Yuangang Gao,Xing Wang
来源: 2019计算智能、工程与信息技术世界大会 2019-06-29
年度: 2019
分类: 基础科学,工程科技Ⅰ辑
专业: 数学,轻工业手工业
单位: School of Electrical and Information Engineering,Zhengzhou University of Light Industry
分类号: TS11;O224
DOI: 10.26914/c.cnkihy.2019.048850
页码: 1320-1326
总页数: 7
文件大小: 335k
下载量: 1
本文来源: https://www.lunwen90.cn/article/36bd7ae1021b8b1e1f25598f.html