TY - JOUR
A2 - Tong, Yao
AU - Peng, Lian
AU - Zou, Hui-Qin
AU - Bauer, Rudolf
AU - Liu, Yong
AU - Tao, Ou
AU - Yan, Su-Rong
AU - Han, Yu
AU - Li, Jia-Hui
AU - Ren, Zhi-Yu
AU - Yan, Yong-Hong
PY - 2014
DA - 2014/06/19
TI - Identification of Chinese Herbal Medicines from Zingiberaceae Family Using Feature Extraction and Cascade Classifier Based on Response Signals from E-Nose
SP - 963035
VL - 2014
AB - Identification of Chinese herbal medicines (CHMs) by human experience is often inaccurate because individual ability and external factors may influence the outcome. However, it might be promising to employ an electronic nose (E-nose) to identify them. This paper presents a rapid and reliable method for identification of ten different species of CHMs from Zingiberaceae family based on their response signals from E-nose. Ten Zingiberaceae CHMs were measured and their maximum response values were analyzed by principal component analysis (PCA). Result shows that E Zhu (Curcuma phaeocaulis Val.) and Yi Zhi (Alpinia oxyphylla Miq.) could not be distinguished completely by PCA. Two solutions were proposed: (i) using BestFirst+CfsSubsetEval (BC) method to extract more discriminative features to select sensors with higher contribution rate and remove the redundant signals; (ii) employing a novel cascade classifier with two stages to enhance the distinguishing-positive rate (DPR). Based on these strategies, six features were extracted and used in different stages of the cascade classifier with higher DPRs.
SN - 1741-427X
UR - https://doi.org/10.1155/2014/963035
DO - 10.1155/2014/963035
JF - Evidence-Based Complementary and Alternative Medicine
PB - Hindawi Publishing Corporation
KW -
ER -