广义回归神经网络在烤烟内在质量分析中的应用  

Application of Generalized Regression Neural Network into Internal Quality Evaluation of Flue-cured Tobaccos

作　　者：何琴[1] 高建华[1] 刘伟[2] 

机构地区：[1]郑州大学化学系,郑州450052 [2]郑州大学生物工程系,郑州450052

出　　处：《安徽农业大学学报》2005年第3期406-410,共5页Journal of Anhui Agricultural University

基　　金：河南省教委自然科学基金项目(9815007)资助。

摘　　要：采用广义回归神经网络分别对烤烟的主要化学成分与香气质、香气量、杂气、刺激、余味、劲头和烟气浓度等感官质量进行建模。结果表明,在训练集样本数据较少时,广义回归神经网络的预测准确度仍然很高。The correlation model between main chemical compositions and sensory qualities of flue-cured tobaccos was constructed by generalized regression neural network(GRNN). The results showed that the prediction accuracy is satisfied,even though there are a few data in training sets.

关 键 词：广义回归神经网络 化学成分 感官质量 烤烟 

分 类 号：O157.5[理学—数学] S572[理学—基础数学]