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

Sensors

Fangfang Qu¹  Dong Ren¹  Jihua Wang¹  Zhong Zhang¹  Na Lu¹  Lei Meng¹ 

[1] College of Computer and Information Technology, Three Gorges University, Yichang 443002, China;

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

DOI  :  10.3390/s16010089

来源: mdpi

【 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.

【 授权许可】

CC BY   
© 2016 by the authors; licensee MDPI, Basel, Switzerland.