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Volumn 44, Issue 4, 2004, Pages 1267-1274

Support vector machines-based quantitative structure-property relationship for the prediction of heat capacity

Author keywords

[No Author keywords available]

Indexed keywords

COMBUSTION; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; NONLINEAR CONTROL SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS;

EID: 4043174776     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci049934n     Document Type: Article
Times cited : (36)

References (28)
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    • Comparison of support vector machine and artificial neural network systems for drug/nNondrug classification
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    • Byvatov, E.1    Fechner, U.2    Sadowski, J.3    Schneider, G.4
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    • Drug design by machine learning: Support vector machines for pharmaceutical data analysis
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    • Liu, H. X.; Zhang, R. S.; Yao, X. J.; Liu, M. C.; Hu, Z. D.; Fan, B. T. QSAR study of ethyl 2-[(3-Methyl-2,5-dioxo(3-pyrrolinyl))amino]-4- (trifluoromethyl) pyrimidine-5-carboxylate: an inhibitor of AP-1 and NF-KB mediated gene expression based on support vector machines. J. Chem. Inf. Comput. Sci. 2003, 43, 1288-1296.
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  • 10
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    • An accurate QSPR study of O-H bond dissociation energy in substituted phenols based on support vector machines
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    • Study of the quantitative structure-mobility relationship of carboxylic acids in capillary electrophoresis based on support vector machines
    • in press
    • Xue, C. X.; Zhang, R. S.; Liu, M. C.; Hu, Z. D.; Fan, B. T. Study of the quantitative structure-mobility relationship of carboxylic acids in capillary electrophoresis based on support vector machines. J. Chem. Inf. Comput. Sci. 2004, in press.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.