上海地区消费者个体特征对休闲服消费倾向的影响分析

在休闲服市场竞争日益激烈的今天，研究消费者个体特征对休闲服消费倾向的影响无疑具有极大的意义。然而消费得不同的个体特征对休闲服消费倾向的影响程度是不同的，这里利用多元线性回归分析探讨了消费者的性别、年龄、学历及年收入对休闲服购买支出、休闲服购买价格及休闲服购买比例等休闲服消费倾向的影响。     

基于BP神经网络的纺纱质量预报模型

简述了纺纱质量预报的理论与实际意义，应用了BP神经网络的标准算法。通过建立BP神经网络模型对细纱条干不匀率(CV）断裂强力(BS)与纺纱断头率(ED)进行预报，并与多元线性回归方法进行比较，验证了BP神经网络预报的准确性与高效性。最后以纺纱断头率(ED)预报为例，指出了今后神经网络在纺纱质量预报应用中亟待解决的问题。     

A Worsted Yarn Virtual Production System Based on BP Neural Network

Back-Propagation (BP) neural network and its modified algorlthm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qua/ides. The results from these two series of models have been compared with the measured values respectively, proving that the accuracy in both the prediction model and the deduction model is high. The experimental results and the corresponding analysis show that the BP neural network is an efficient technique for the quality prediction and has wide prospect in the application of worsted yam production system.