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Volumn 302, Issue 2, 2006, Pages 669-672

The accurate QSPR models for the prediction of nonionic surfactant cloud point

Author keywords

Cloud point; Heuristic method; Nonionic surfactants; Quantitative structure property relationships; Support vector machine

Indexed keywords

CLOUD CHAMBERS; HEURISTIC METHODS; ISOMERIZATION; MATHEMATICAL MODELS; REGRESSION ANALYSIS; SOLUTIONS; VECTORS;

EID: 33748300579     PISSN: 00219797     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jcis.2006.06.072     Document Type: Article
Times cited : (28)

References (15)
  • 9
    • 85083146954 scopus 로고    scopus 로고
    • HyperChem, 2000, Release 6.0 for Windows, Hypercube, Inc
  • 10
    • 85083138004 scopus 로고    scopus 로고
    • A.R. Katritzky, V.S. Lobanov, M. Karelson, CODESSA Version 2.0 Reference Manual, 1995-1997
  • 12
    • 85083147789 scopus 로고    scopus 로고
    • A.J. Smola, B. Schölkopf, A Tutorial on Support Vector Regression, NeuroCOLT2 Technical Report Series, NC2-TR-1998-030, 1998
  • 14
    • 85083152656 scopus 로고    scopus 로고
    • LIBSVM-A Library for Support Vector Machines; available at:
    • Chang C.C., and Lin C.J. LIBSVM-A Library for Support Vector Machines; available at:. http://www.csie.ntu.edu.tw/~cjlin/libsvm/
    • Chang, C.C.1    Lin, C.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.