DocumentCode :
2766815
Title :
Research on data mining methods for organoleptic determination of Amomum villosum product
Author :
Wen-Guang, Zhao ; Chao-fan, Yu ; Ruo-Ting, Zhan ; Rui, He
Author_Institution :
Inst. of Inf. Technol., Guangzhou Univ. of Chinese Med., Guangzhou, China
fYear :
2011
fDate :
12-15 Nov. 2011
Firstpage :
873
Lastpage :
880
Abstract :
Based on ideas and methods of organoleptic evaluation on agricultural commodities, the article establishes the quantitative indicators that can make effect evaluation and control of the level of Chinese herbal product specifications for the herb Amomum. Combined with IT technology, we analyze and modeling the experimental data to explore the generation of a practical, scientific and standardized method of Amomum organoleptic evaluation. The application of robust regression in the research to produce the prediction model achieved the classification forecast of Amomum product specifications.
Keywords :
agricultural products; data mining; health care; pharmaceuticals; regression analysis; Amomum organoleptic evaluation; Amomum product specification; Amomum villosum product; Chinese herbal product specification; IT technology; agricultural commodity; data mining; herb Amomum; organoleptic determination; quantitative indicator; robust regression; Analytical models; Data mining; Data models; Databases; Equations; Mathematical model; Predictive models; Amomum villosum; data mining; organoleptic determination;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1612-6
Type :
conf
DOI :
10.1109/BIBMW.2011.6112489
Filename :
6112489
Link To Document :
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