%0 Journal Article
%T Soft Sensor Modeling Based on a Modified k-Nearest Neighbor Regression Algorithm<br>基于改进k-最近邻回归算法的软测量建模
%A YE Tao
%A ZHU Xue-Feng
%A LI Xiang-Yang
%A SHI Bu-Hai
%A <br>叶涛
%A 朱学峰
%A 李向阳
%A 史步海
%J 自动化学报
%D 2007
%I 
%X Recently,machine learning regression algorithms are widely applied to soft sensor modeling for complex industrial processes.The k-nearest neighbor(kNN)algorithm is a popular learning algorithm for solving regression problems.However,the traditional kNN algorithm has low efficiency and ignores the fea- ture weights in distance computing.Using a quadratic distance definition and a data set editing algorithm,we have modified the traditional kNN regression algorithm.The modified algorithm is applied to soft sensor modeling and some useful conclusions are reached.
%K k-nearest neighbor algorithm
%K quadratic distance
%K soft sensing
%K pulp Kappa number<br>k-最近邻算法
%K 二次型距离
%K 软测量
%K 纸浆Kappa值
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=B5947D32AEB89467&yid=A732AF04DDA03BB3&vid=27746BCEEE58E9DC&iid=9CF7A0430CBB2DFD&sid=112A5CAF55F27887&eid=E6D5A068841F33F3&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=11