Prediction of fungicidal activities of rice blast disease based on least-squares support vector machines and project pursuit regression

Journal of Agricultural and Food Chemistry

Volumn 56, Issue 22, 2008, Pages 10785-10792

  Du, Hongying ^a   Wang, Jie ^a,b   Hu, Zhide ^a   Yao, Xiaojun ^a   Zhang, Xiaoyun ^a  

^a LANZHOU UNIVERSITY   (China)

^b Yale University   (United States)

Author keywords

Fungicidal activity; Genetic algorithm (GA); Least squares support vector machine (LS SVM); Projection pursuit regression (PPR); Quantitative structure activity relationship (QSAR)

Indexed keywords

FUNGICIDE; THIAZOLE DERIVATIVE;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMISTRY; DRUG DESIGN; DRUG EFFECT; MAGNAPORTHE; MICROBIOLOGY; PLANT DISEASE; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REGRESSION ANALYSIS; RICE; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DRUG DESIGN; FUNGICIDES, INDUSTRIAL; LEAST-SQUARES ANALYSIS; LINEAR MODELS; MAGNAPORTHE; ORYZA SATIVA; PLANT DISEASES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; THIAZOLES;

EID: 57849090595     PISSN: 00218561     EISSN: None     Source Type: Journal    
DOI: 10.1021/jf8022194     Document Type: Article

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