pKa modeling and prediction of a series of pH indicators through genetic algorithm-least square support vector regression

Chemometrics and Intelligent Laboratory Systems

Volumn 101, Issue 2, 2010, Pages 102-109

  Goodarzi, Mohammad ^a,d   Freitas, Matheus P ^b   Wu, Chih H ^c   Duchowicz, Pablo R ^a  

^a INSTITUTO DE INVESTIGACIONES FISICOQUÍMICAS TEÓRICAS Y APLICADAS INIFTA   (Argentina)

^b FEDERAL UNIVERSITY OF LAVRAS   (Brazil)

^c NATIONAL TAICHUNG UNIVERSITY OF EDUCATION   (Taiwan)

^d ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

GA LSSVR; PH indicators; pKa; Quantitative structure property relationships; Support vector machines

Indexed keywords

ACCURACY; ANALYTIC METHOD; ARTICLE; CONTROLLED STUDY; GENETIC ALGORITHM; INTERMETHOD COMPARISON; LINEAR SYSTEM; MATHEMATICAL COMPUTING; NONLINEAR SYSTEM; PH; PHYSICAL CHEMISTRY; PKA; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINE;

EID: 77951090353     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2010.02.003     Document Type: Article

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