%0 Journal Article
%T Intelligent Prediction Method for Small-Batch Producing Quality based on Fuzzy Least Square SVM<br>基于模糊支持向量机的小批量生产质量智能预测方法
%A DONG Hua
%A YANG Shi-yuan
%A WU De-hui
%A <br>董 华
%A 杨世元
%A 吴德会
%J 系统工程理论与实践
%D 2007
%I 
%X A quality intelligent prediction model for small-batch producing process was proposed in the paper,after comparing with the common used approaches of procedure intelligent prediction and their characteristics.The prediction process and algorithm were presented too.The model takes fuzzy least square support vector machine(FLS-SVM) as the intelligent kernel.On one hand,it can solve the small-batch learning better and avoid the disadvantages,such as over-trainning,weak normization capability,etc.,of artificial neural networks prediction.On the other hand,it makes samples fuzzy by membership function to choose optimum samples and make history data 'farther is more weight'.After doing lots of prediction experiments and comparing with other common prediction methods,the method proposed in the paper proved to be good normization capability,more rapidly built,and more easily realized.It offers feasibility to predict and control small-batch machining process online.
%K small-batch
%K support vector machine(SVM)
%K fuzzy least square support vector machine(FLS-SVM)
%K intelligent prediction
%K quality control<br>小批量
%K 支持向量机
%K 模糊支持向量机
%K 智能预测
%K 质量控制
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=BA83443E33ED0775&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=38B194292C032A66&sid=10F298ED9F164662&eid=DBF54A8E2A721A6D&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=0&reference_num=10