Soft Sensor Modeling Based on a Modified k-Nearest Neighbor Regression Algorithm
基于改进k-最近邻回归算法的软测量建模

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.