云南化工Issue(1)：45-47,3.DOI:12.3969/j.issn.1004-275X.2015.01.012
基于主成分分析和偏最小二乘回归的烟煤水分近红外检测
NIR Detecting of Bituminous Coal Moisture Based on Main Components Analysis and Partial Least Squares Regression Analysis
摘要
Abstract
Based on Near Infrared Spectroscopy for bituminous coal moisture detection with rapid,non-destructive characters.the collected 100 samples of bituminous coal were divided into two sets,one is vali-dation set and another is prediction set,85 for validation set 15 for the prediction set.Analysis of bituminous coal the near infrared spectroscopy data were compressed via the main components′analysis,and then the main ingredients were entered,using partial least squares regression,the predict model of bituminous coal moisture was established.Bituminous coal moisture mean absolute relative error was 0.0728,indicating that the method for predicting the moisture content of the bituminous coal was feasible.关键词
近红外/烟煤/水分/检测/主成分分析/偏最小二乘回归Key words
near infrared spectroscopy/moisture/main component analysis/bituminous partial least squares regression分类
化学化工引用本文复制引用
马公喆,杨晓丽,汪文超,陈云秀..基于主成分分析和偏最小二乘回归的烟煤水分近红外检测[J].云南化工,2015,(1):45-47,3.基金项目
云南省省级大学生创新创业训练计划项目（编号201310664003）。 （）
