title: Rapid Identification of Asteraceae Plants with Improved RBF-ANN Classification Models Based on MOS Sensor E-Nose.
abstract: Plants from Asteraceae family are widely used as herbal medicines and food ingredients, especially in Asian area. Therefore, authentication and quality control of these different Asteraceae plants are important for ensuring consumers' safety and efficacy. In recent decades, electronic nose (E-nose) has been studied as an alternative approach. In this paper, we aim to develop a novel discriminative model by improving radial basis function artificial neural network (RBF-ANN) classification model. Feature selection algorithms, including principal component analysis (PCA) and BestFirst + CfsSubsetEval (BC), were applied in the improvement of RBF-ANN models. Results illustrate that in the improved RBF-ANN models with lower dimension data classification accuracies (100%) remained the same as in the original model with higher-dimension data. It is the first time to introduce feature selection methods to get valuable information on how to attribute more relevant MOS sensors; namely, in this case, S1, S3, S4, S6, and S7 show better capability to distinguish these Asteraceae plants. This paper also gives insights to further research in this area, for instance, sensor array optimization and performance improvement of classification model.
authors.affiliation: Library, Beijing University of Chinese Medicine, No. 11 Bei San Huan Dong Lu, Chaoyang District, Beijing 100029, China.
authors.forename: Hui-Qin
authors.initials: HQ
authors.lastname: Zou
authors.affiliation: Beijing University of Posts and Telecommunications, No. 10 Xi Tu Cheng Lu, Haidian District, Beijing 100876, China.
authors.forename: Shuo
authors.initials: S
authors.lastname: Li
authors.affiliation: Library, Beijing University of Chinese Medicine, No. 11 Bei San Huan Dong Lu, Chaoyang District, Beijing 100029, China.
authors.forename: Ying-Hua
authors.initials: YH
authors.lastname: Huang
authors.affiliation: School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wang Jing Zhong Huan Nan Lu, Chaoyang District, Beijing 100102, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Institute of Pharmaceutical Sciences, University of Graz, Universitaetsplatz 4, 8010 Graz, Austria.
authors.forename: Rudolf
authors.initials: R
authors.lastname: Bauer
authors.affiliation: School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wang Jing Zhong Huan Nan Lu, Chaoyang District, Beijing 100102, China.
authors.forename: Lian
authors.initials: L
authors.lastname: Peng
authors.affiliation: School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wang Jing Zhong Huan Nan Lu, Chaoyang District, Beijing 100102, China.
authors.forename: Ou
authors.initials: O
authors.lastname: Tao
authors.affiliation: School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wang Jing Zhong Huan Nan Lu, Chaoyang District, Beijing 100102, China.
authors.forename: Su-Rong
authors.initials: SR
authors.lastname: Yan
authors.affiliation: School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wang Jing Zhong Huan Nan Lu, Chaoyang District, Beijing 100102, China.
authors.forename: Yong-Hong
authors.initials: YH
authors.lastname: Yan