Intelligent technology for Correlation Analysis of Tar in Tobacco

Author

Lin-Tao Ma ; Xiang-Qian Ding ; Ning Yang ; Hui-Li Gong

Author_Institution

Inf. Eng. Center, Ocean Univ. of China, Qingdao

fYear

2006

fDate

4-6 Oct. 2006

Firstpage

1537

Lastpage

1542

Abstract

Smoking is harmful to our health, and tar is one of the main substance should be paid attention to. We can greatly reduce serious risks to human health by finding the correlation between chemical elements in tobacco leaf and tar. We introduce intelligent algorithms as support vector machine (SVM), M5´ model tree, information diffusion technique and PCA, to do the correlation analysis, and combine them with traditional analytical method. Experiment results indicate the efficiency

Keywords

artificial intelligence; chemical engineering computing; diffusion; principal component analysis; support vector machines; tobacco industry; M5 model tree; chemical elements; correlation analysis; human health; information diffusion; intelligent technology; principal component analysis; support vector machine; tobacco leaf; tobacco tar; Algorithm design and analysis; Chemical analysis; Computational intelligence; Data analysis; Information analysis; Marine technology; Oceans; Principal component analysis; Support vector machines; Systems engineering and theory; Correlation Analysis; Information Diffusion Technique; M5´ model tree; Support Vector Machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Engineering in Systems Applications, IMACS Multiconference on

Conference_Location

Beijing

Print_ISBN

7-302-13922-9

Electronic_ISBN

7-900718-14-1

Type

conf

DOI

10.1109/CESA.2006.313559

Filename

4105625