一种近红外光谱特征子区间选择新算法  

A New Method of Characteristic Wavelength Sub-Range Selection of Near Infrared Spectroscopy

作　　者：石吉勇[1] 邹小波[1] 赵杰文[1] 殷晓平[1] 陈正伟[1] 

机构地区：[1]江苏大学食品与生物工程学院,江苏镇江212013

出　　处：《光谱学与光谱分析》2010年第12期3199-3202,共4页Spectroscopy and Spectral Analysis

基　　金：国家(863计划)项目(2006AA10Z208);国家自然科学基金项目(60901079);江苏省六大人才高峰和青蓝工程项目;国家博士后基金项目;优秀博士论文基金项目;江苏省普通高校研究生科研创新计划项目资助

摘　　要：为了简化光谱模型和提高模型精度,在传统遗传算法中引入Metropolis接受准则,提出了一种新的模拟退火-遗传区间选择算法(SAA-GA-iPLS),用于快速提取近红外光谱特征子区间,采用偏最小二乘法(PLS)建立近红外光谱模型。以黄瓜叶近红外光谱数据及其类胡萝卜素含量为例,将全光谱分为40个区间,模拟退火-遗传算法能快速优选出7个子区间(分别为第3,5,14,18,21,32,33子区间),在所选7个子区间的基础上建立了黄瓜叶类胡萝卜素PLS光谱模型。与传统遗传算法的比较结果表明:无论是建模效果还是算法执行效率,模拟退火-遗传算法均优于传统遗传算法。To improve and simplify the prediction model of carotenoid content of cucumber leaves,genetic algorithm（GA） combined with Metropolis acceptance criterion of simulated annealing algorithm（SAA） as well as interval partial least square（iPLS） were proposed and used to establish the calibration models of carotenoid content against cucumber leaves spectra.The cucumber leaves spectra data were divided into 40 intervals,among which 7 subsets,i.e.No.3,4,14,18,21,32 and 33,were selected by SAA-GA-iPLS.The comparison was made between SAA-GA-iPLS and traditional genetic algorithm interval partial least square（GA-iPLS）,and the result of this study shows that SAA-GA-iPLS was better than traditional genetic algorithm interval partial least square（GA-iPLS）.

关 键 词：遗传算法 模拟退火算法 近红外光谱 类胡萝卜素 黄瓜叶 

分 类 号：O242.23[理学—计算数学] S123[理学—数学]