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An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor

文献类型： 外文期刊

作者： Qu, Fangfang 1 ; Ren, Dong 1 ; Wang, Jihua 1 ; Zhang, Zhong 1 ; Lu, Na 1 ; Meng, Lei 1 ;

作者机构： 1.Three Gorges Univ, Coll Comp & Informat Technol, Yichang 443002, Peoples R China

2.Beijing Res Ctr Agr Stand & Testing, Beijing 100097, Peoples R China

关键词： near infrared sensors;information processing;spectroscopy;variable selection;successive projections algorithm

期刊名称：SENSORS （ 影响因子：3.576； 五年影响因子：3.735 ）

ISSN： 1424-8220

年卷期： 2016 年 16 卷 1 期

页码：

收录情况： SCI

摘要： Spectral analysis technique based on near infrared (NIR) sensor is a powerful tool for complex information processing and high precision recognition, and it has been widely applied to quality analysis and online inspection of agricultural products. This paper proposes a new method to address the instability of small sample sizes in the successive projections algorithm (SPA) as well as the lack of association between selected variables and the analyte. The proposed method is an evaluated bootstrap ensemble SPA method (EBSPA) based on a variable evaluation index (EI) for variable selection, and is applied to the quantitative prediction of alcohol concentrations in liquor using NIR sensor. In the experiment, the proposed EBSPA with three kinds of modeling methods are established to test their performance. In addition, the proposed EBSPA combined with partial least square is compared with other state-of-the-art variable selection methods. The results show that the proposed method can solve the defects of SPA and it has the best generalization performance and stability. Furthermore, the physical meaning of the selected variables from the near infrared sensor data is clear, which can effectively reduce the variables and improve their prediction accuracy.

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