Rapid Recognition of Different Sources of Heroin Drugs by Using a Hand-Held Near-Infrared Spectrometer Based on a Multi-Layer Extreme Learning Machine Algorithm

Journal of the Brazilian Chemical Society

article

Jianqiang, Zhang¹  Chunming, Ni¹  Chengyun, Peng¹  Junxun, Hu¹  Sheng, Gao¹  Jin, Chen¹ 

[1] Yunnan Police College

关键词: hand-held near-infrared spectroscopy;    multi-layer-extreme learning machine;    heroin drugs;    drug source;   

DOI  :  10.21577/0103-5053.20220120

学科分类：内科医学

来源: SciELO

【 摘 要 】

Rapid recognition of the sources of drugs can provide some valuable clues and the basis for determining the nature of the case. A novel recognition method was put forward to identify the sources of heroin drugs rapidly and non-destructively by using a hand-held near infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. In contrast to traditional linear discriminant analysis (LDA), support vector machine (SVM) and extreme learning machine (ELM) algorithms, the accuracy, sensitivity and specificity were the highest for the proposed ML-ELM algorithm. The prediction accuracy of the ML-ELM algorithm was 25.33, 20.00, 17.33% higher than that of LDA, SVM and ELM algorithm, respectively, for 4 cases. The ML-ELM models for recognizing the different sources of heroin drugs had the best generalization ability and prediction results. The experimental results indicated that the combination of the hand held NIR technology and ML-ELM algorithm can recognize the different sources of heroin drugs rapidly, accurately, and non-destructively on the spot.

【 授权许可】

CC BY