Classi¢cation of organic solvents and modelling of their physico-chemical properties by chemometric methods using different sets of molecular descriptors
نویسندگان
چکیده
Different sets of molecular descriptors using the k-nearest neighbor classi¢cation method were used to make a general classi¢cation of 152 organic solvents, the classi¢cation being further improved by performing the counterpropagation arti¢cial neural network. An extensive investigation was made of the physico-chemical properties of 152 solvents in a search for quantitative structure^property relationships (QSPR). Wide sets of molecular descriptors were tested and regression models were obtained by selecting the best descriptor subset by genetic algorithm in order to optimize their prediction power. z1999 Elsevier Science B.V. All rights reserved.
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