文献类型：期刊文献

中文题名：混合蚁群算法及其用于有机物毒性的QSAR研究

英文题名：Hybrid ant colony algorithm and its application to QSAR for toxicities of organic substance

作者：张小广[1];李绍军[1];刘漫丹[1]

机构：[1]华东理工大学自动化研究所,上海200237

年份：2009

卷号：26

期号：5

起止页码：549

中文期刊名：计算机与应用化学

外文期刊名：Computers and Applied Chemistry

收录：CSTPCD;;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：国家863计划(2007AA04Z171);上海市重点学科建设项目(编号:B504);上海市自然科学基金(06ZR14027)

语种：中文

中文关键词：蚁群算法;PBIL;神经网络;QSAR

外文关键词：ant colony algorithm （ACA）, population based incremental learning （PBIL）, neural network, QSAR

摘要：设计一种新的混合蚁群算法。该算法以一种新的二进制蚁群算法为基础,混合PBIL(population based incremental learning)算法及遗传算法的交叉操作和变异操作,从而大大提高了种群的多样性及收敛速度,改善全局最优解的搜索能力。通过函数优化测试,表明该算法具有良好的收敛速度和稳定性,最后用于有机物毒性的QSAR研究中,取得较好效果。
A kind of new hybrid ant colony algorithm was designed. It uses a new binary ant colony algorithm as the basis, combining with PBIL and the crossover operation and the mutation operation of GA, thus greatly raising its population polymorphism and speedy convergence rate, and improving the searching ability of the overall optimal solution. Functions optimization tests show that the hybrid algorithm has fine convergence rate and stability. Good results are obtained by applying this algorithm to the modeling of QSAR for toxicities of organic substance.