MODIFIED ANT COLONY OPTIMIZATION ALGORITHM AND ITS APPLICATION IN VARIABLE SELECTION OF QSAR OF POLYCHLORINATED ORGANIC COMPOUNDS-Reference-Cited by-同舟云学术

MODIFIED ANT COLONY OPTIMIZATION ALGORITHM AND ITS APPLICATION IN VARIABLE SELECTION OF QSAR OF POLYCHLORINATED ORGANIC COMPOUNDS

Published:2009-10 Issue:05 Volume:08 Page:783-798
ISSN:0219-6336
Container-title:Journal of Theoretical and Computational Chemistry
language:en
Short-container-title:J. Theor. Comput. Chem.

Author:

ZHANG YONGQING¹,HUANG XIANG¹,JIANG XU¹,HUANG SHAOBIN¹

Affiliation:

1. College of Environmental Science and Engineering, South China University of Technology, Guangzhou, 510006, China

Abstract

A modified ant colony optimization (ACO) algorithm was used for the selection of the variables that result in the best-fitted models for the bioconcentration factor (BCF) of polychlorinated organic compounds (PCOCs). The fitness function of the modified ACO is discussed in detail and a new expression for the fitness function is presented. The modified ACO is applied in quantitative structure–activity relationships of selected PCOCs for predicting BCFs and the best-fitting models by the ACO were obtained. The convergence velocity was acceptable.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Physical and Theoretical Chemistry,Computer Science Applications

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0219633609005143

Reference26 articles.

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