%0 Journal Article
%T Flatness defect pattern recognition with data mining technology<br>基于数据挖掘技术的板形缺陷模式识别
%A ZHAO Xiao-yan
%A ZHANG Zhao-hui
%A <br>赵小燕
%A 张朝晖
%J 计算机应用
%D 2009
%I 
%X The flatness defect pattern recognition based on data mining technology was proposed. In order to solve low accuracy of normal BP (Back Propagation) network, a novel data mining algorithm based on hierarchical BP model was presented. The new model with binary tree structure reduced prediction range of each network and adopted several networks for degree elevation. Compared with the normal BP model, the new system precision was improved remarkably. The experimental results show this method can meet the requirements of the producing process.
%K data mining
%K artificial neural network
%K flatness defect
%K pattern recognition
%K hierarchy<br>数据挖掘
%K 人工神经网络
%K 板形缺陷
%K 模式识别
%K 分层
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=7E17393755852B8CFA26DFDC05EF0379&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=38B194292C032A66&sid=FC6FCA5A7559F1FB&eid=97747634025A5F36&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=10