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Optimization of Carbó molecular similarity index using gradient methods
Author(s) -
McMahon Alan J.,
King Paul M.
Publication year - 1997
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/(sici)1096-987x(19970130)18:2<151::aid-jcc1>3.0.co;2-u
Subject(s) - similarity (geometry) , gradient descent , simplex , index (typography) , gradient method , computer science , simplex algorithm , mathematics , algorithm , mathematical optimization , artificial intelligence , linear programming , combinatorics , world wide web , image (mathematics) , artificial neural network
A steepest descent method for optimizing the Carbó molecular similarity index was implemented and evaluated. Comparisons were made between this procedure and the extensively used simplex method. Several data sets were considered, and in each case the gradient method showed a substantial improvement in the time taken for the optimization to converge while comparable similarity values were obtained. In some cases, performance enhancements of up to an order of magnitude were observed. © 1997 by John Wiley & Sons, Inc.