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Molecular parameter optimization using simulated annealing and evolutionary algorithm techniques in a quantum parametric method (CATIVIC)

机译:在量子参数方法(CATIVIC)中使用模拟退火和进化算法技术进行分子参数优化

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摘要

Application of simulated annealing (SA) and evolutionary algorithm (EA) techniques for optimization of parameters in the parametric quantum chemistry method (CATIVIC) was performed. A set of organic molecules and gold clusters were selected for test these techniques. Comparison was performed with respect to experimental values and DFT calculated equilibrium bond distances (EBD) and bond angles (BA). Results show that EA is more efficient than SA with respect to computer time. Accuracy is similar in both methods; however, there are important differences in the set of parameters.
机译:应用了模拟退火(SA)和进化算法(EA)技术优化了参数量子化学方法(CATIVIC)中的参数。选择了一组有机分子和金簇来测试这些技术。比较实验值和DFT计算的平衡键距(EBD)和键角(BA)。结果表明,就计算机时间而言,EA比SA更有效。两种方法的准确性相似。但是,参数集存在重要差异。

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