Intelligent Algorithms for Tobacco-leaf Correlation Analysis

Intelligent Algorithms for Tobacco-leaf Correlation Analysis

Directing against the data environment with complicated relations and few data of tobacco industry, we introduce intelligent algorithms as support vector machine (SVM), M5' model tree and information diffusion technique, to the tobacco-leaf correlation analysis, and combine them with traditiona...

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Bibliographische Detailangaben
Hauptverfasser: Xue-Yan Song, Rui Hu, Tian-Jin Feng, Xiang-Qian Ding, Ying He
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Algorithm design and analysis
Appraisal
Chemical analysis
Chemical industry
Chemical processes
Data engineering
Helium
Information analysis
Information Diffusion Technique
M5' model tree
Support Vector Machine
Support vector machines
Testing
tobacco-leaf correlation analysis
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Beschreibung
Zusammenfassung:Directing against the data environment with complicated relations and few data of tobacco industry, we introduce intelligent algorithms as support vector machine (SVM), M5' model tree and information diffusion technique, to the tobacco-leaf correlation analysis, and combine them with traditional analytical method. Experiment result indicates the efficiency
DOI:10.1109/ICNNB.2005.1614783