基于变量选择的蚕茧茧层量可见-近红外光谱无损检测
以蚕茧茧层量为研究对象,研究了基于可见-近红外光谱技术的蚕茧茧层量无损检测方法。采用最小二乘支持向量机(least square-support vector machine,LS-SVM)建立可见-近红外光谱模型。采用无信息变量消除算法(uninformative variable elimination,UVE)与连续投影算法(successive projections algorithm,SPA)相结合选取光谱有效波长。结果表明,基于UVE-SPA法进行变量选择,最终将原始光谱的600个光谱变量减少到了8个(673,937,963,982,989,992,995和1008nm)。基于此...
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Published in | Nong ye gong cheng xue bao Vol. 26; no. 2; pp. 231 - 236 |
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Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
浙江大学动物科学学院,杭州,310029%浙江大学生物系统工程与食品科学学院,杭州,310029%浙江省湖州市农业科学研究院,湖州,313000
2010
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Subjects | |
Online Access | Get full text |
ISSN | 1002-6819 |
DOI | 10.3969/j.issn.1002-6819.2010.02.040 |
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Summary: | 以蚕茧茧层量为研究对象,研究了基于可见-近红外光谱技术的蚕茧茧层量无损检测方法。采用最小二乘支持向量机(least square-support vector machine,LS-SVM)建立可见-近红外光谱模型。采用无信息变量消除算法(uninformative variable elimination,UVE)与连续投影算法(successive projections algorithm,SPA)相结合选取光谱有效波长。结果表明,基于UVE-SPA法进行变量选择,最终将原始光谱的600个光谱变量减少到了8个(673,937,963,982,989,992,995和1008nm)。基于此8个变量建立的LS-SVM模型得到了预测集的确定系数(Rp^2)为0.5354,误差均方根(RMSEP)为0.0373的预测结果。表明可见-近红外光谱可以用于对蚕茧的茧层量进行无损检测,同时UVE-SPA是一种有效的光谱变量选择方法。 |
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Bibliography: | nondestructive examination model analysis 11-2047/S S886.3 near infrared spectroscopy cocoon shell weight uninformative variable elimination(UVE) near infrared spectroscopy; nondestructive examination; model analysis; cocoon; shell weight; uninformative variable elimination(UVE); successive projections algorithm(SPA) successive projections algorithm(SPA) O657.3 |
ISSN: | 1002-6819 |
DOI: | 10.3969/j.issn.1002-6819.2010.02.040 |