Please wait a minute...
浙江大学学报（农业与生命科学版）
Journal of Zhejiang University: Agric. & Life Sci.  2011, Vol. 37 Issue (4): 453-459    DOI: 10.3785/j.issn.1008-9209.2011.04.015
Agricultural sciences     
Application of quantum-inspired evolutionary algorithm in the analysis of near infrared diffuse transmission spectroscopy of apples .
LI Jun-liang,WANG Cong-qing
College of Automation Engineering , Nanjing University of Aeronautics and Astronautics , Nanjing 210016 , China）
Download: HTML ( )    PDF(1157KB)
Export: BibTeX | EndNote (RIS)      

Abstract  To study the application of quantum‐inspired evolutionary algorithm (QEA) in the analysis of near infrared ( NIR) diffuse transmission spectroscopy of apples , first , spectroscopy regions were preselected by using the backward interval partial least squares (BiPLS) . Second , the variables were selected with QEA , and QEA‐PLS model was built . Meanwhile , genetic algorithm ( GA) -PLS model was developed to contrast with QEA‐PLS model . After running GA and QEA １０ times separately , the
two best models were chosen from the １０ GA-PLS models and the １０ QEA‐PLS models . The results showed that the GA‐PLS model had １１０ variables , with RMSEC ( root mean standard error of calibration) of ０.５８２ ０ , RMSEP (root mean standard error of prediction) of ０.６１２ ３ , but the QEA‐PLS model had １９４ variables ,with RMSEC of ０.４９２ ７ , RMSEP of ０.５２６ ０ . It is concluded that QEA can be used in the analysis of NIR diffuse transmission spectroscopy of apples and enhance the precision of model . Compared to GA , search capability of QEA is better .

Published: 20 July 2011
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
LI Jun-liang
WANG Cong-qing
Cite this article:

LI Jun-liang,WANG Cong-qing. Application of quantum-inspired evolutionary algorithm in the analysis of near infrared diffuse transmission spectroscopy of apples .. Journal of Zhejiang University: Agric. & Life Sci., 2011, 37(4): 453-459.

URL:

http://www.zjujournals.com/agr/10.3785/j.issn.1008-9209.2011.04.015     OR     http://www.zjujournals.com/agr/Y2011/V37/I4/453


量子进化算法在苹果漫透射近红外光谱分析中的应用

为了研究量子进化算法(quantum‐inspired evolutionary algorithm ,QEA) 在苹果漫透射近红外光谱分析中的应用,先用反向间隔偏最小二乘法(backward interval partial least squares ,BiPLS) 对光谱信息区间初步定位,再采用QEA 算法选择波长点,建立糖度预测模型;同时采用遗传算法( genetic algorithm , GA)选取波长点建立预测模型,并对２ 种算法的结果进行比较.结果表明:运行GA 算法建立的GA‐PLS 模型变量数为１１０ ,校正均方根误差( root mean standard error of calibration , RMSEC) 为０ .５８２ ０ ,预测均方根误差( root mean standard error of prediction , RMSEP) 为０ .６１２ ３ ;运行QEA 算法建立的QEA‐PLS 模型变量数为１９４ ,RMSEC 为０ .４９２ ７ ,RMSEP 为0.5260.说明量子进化算法用于苹果漫透射近红外光谱分析可有效提高模型预测精度,相比遗传算法表现出更好的寻优能力.
No related articles found!