Acanthopanax senticosus Harms Intelligence Quality Assessment Based on Core Data

Jian Yang Lin; Yong Yu; Ya Jie Xu; Zhou Mi Kan

doi:10.4028/www.scientific.net/AMR.383-390.4938

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 383-390Acanthopanax senticosus Harms Intelligence Quality...

Acanthopanax senticosus Harms Intelligence Quality Assessment Based on Core Data

Abstract:

According to the traditional morphological classification divide the quality of traditional Chinese medicine Acanthopanax Senticosus Harms into recommended products non-recommended products and shoddy goods distribute the chromatogram data Acanthopanax Senticosus Harms obtained in the condition of standard inspect and abstract main data and get the great peaks of linear independent vectors. Get Acanthopanax Senticosus Harms every clustering centre data with liner reduction PSO and Conjugate gradient optimization. Make Acanthopanax Senticosus Harms criterion data as Gamma distribution and calculate similar by the sample data Normal distribution and ensure the finial similar by angle cosine. That will use lada integral and upper gauss interpolation. It need to calculate the similar between unknown sample and the common pattern of corresponding sample when analyze unknown sample. Make appraise classify and evaluate to unknown sample and make good identification to counterfeit medofenoxate for example gracilistylus koxmo hoo column5 plus fine.

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Manufacturing Science and Technology, ICMST2011

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Periodical:

Advanced Materials Research (Volumes 383-390)

Pages:

4938-4943

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.383-390.4938

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Online since:

November 2011

Authors:

Jian Yang Lin, Yong Yu, Ya Jie Xu, Zhou Mi Kan

Keywords:

Acanthopanax senticosus Harms, Core Data, Distribution Clustering, Quality Assessment

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References

[1] B L Tan. Rough set theory analysis and applied research [J]. China CIO News, 2009, 12(10): 75-78.

Google Scholar

[2] C Gong, Z L Wang. Proficient optimization calculation in Matlab[M]. Beijing: Publishing house of electronics industry, 2009: 279-280.

Google Scholar

[3] G Y He. VB commonly used algorithm daquan[M]. Xi'an: Xi'an electronic technology university press, 2001: 347.

Google Scholar

[4] Y M Zhang. Reliable design of vehicle spare-parts [M]. Beijing: Beijing Institute of Technology Press, 2000, 71-72.

Google Scholar

[5] X Wang, W Y Wang, K R Zhang, etc. Aproaching the study on the similarity analysis of HPLC fingerprints spectra china medinicens[J]. Journal of Shenyang Pharmaceutica, 2003, 20(5): 361-362.

Google Scholar

[6] C Gong，Z L Wang. MATLAB assembly language commonly used algorithm [M]. Beijing: Publishing House of Electronics Industry, 2008: 79, 196-197.

Google Scholar

[7] X R Yuan. Study on the Method of Quality Control of Acanthopanax Senticosus Harms [D]. Shenyang: Shenyang pharmaceutical university, 2004: 47-50.

Google Scholar

[8] D Y Xue, Y Q Chen. Matlab solution for the advanced mathematic program [M]. Beijing: Tsinghua，2008: 365-368.

Google Scholar