北京工商大学学报：自然科学版2011，Vol.29Issue(4)：64-67,4.
BP神经网络在ATR．FTIR技术微量农药溶液检测中的应用
Application of BP Neural Network in Detecting Trace Pesticide Solution Based on ATR-FTIR Technology
摘要
Abstract
ATR-FTIR technology was used in this article to detect trace element solution of Chlorpyrifos and Propargite separately. Subtraction, baseline correction and vector normalization was used to prepro- cess the spectrum data. The quantitative analysis models of Chlorpyrifos and Propargite solution were established using the function traingdx and trainscg of MATLAB BP Neural Network toolbox. The experiment results showed that for the chlorpyrifos determination, the correlation coefficient was 0. 998 6, root mean square error of cross validation was 0. 100 0, and root mean square error of prediction was 0. 220 1 ; for the propargite determination, the correlatin coefficient was 0. 997 4, root mean square error of cross validation was 0. 391 8, and root mean square error of prediction was 0. 624 1. As results indicated, application of BP Neural Network in detecting trace pesticide solution based on ATR-FTIR Technology was a quick and precisely method with good generalization ability.关键词
BP神经网络/ATR-FTIR/农药残留/毒死蜱/炔螨特Key words
BP neural network/ATR-FTIR/pesticide residue/chlorpyrifos/propargite分类
轻工纺织引用本文复制引用
刘翠玲,索少增,吴静珠,孙晓荣,吴胜男,苏淼..BP神经网络在ATR．FTIR技术微量农药溶液检测中的应用[J].北京工商大学学报：自然科学版,2011,29(4):64-67,4.基金项目
北京市自然科学基金项目 （）
北京市优秀人才资助项目 （）
