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采用量子化学从头算方法在HF/6-311+G(d)水平上计算8种烷基酚类化合物的分子结构描述符,选用修正过的C_p统计量为目标函和新蚁群优化算法,于烷基酚类化合物的定量结构——活性相关研究中的变量选择,建立烷基酚类化合物的生物降解速率常数与其量化参数之间的QSAR模型。结果表明,新蚁群优化算法用于定量构效中的变量选择比较简单,而且需要调节的参数少,是变量选择的有用方法,且应用量子化学结构参数建模的相关系数R =0.994,与文献中R=0.982相比相关性更好。
Molecular structure descriptors of eight alkylphenols were calculated by ab initio method at HF / 6-311 + G (d) level. The modified C_p statistic was used as the objective function and a new ant colony optimization algorithm. In the quantitative structure-activity correlation studies of alkylphenols, the QSAR model was established to establish the biodegradation rate constant of alkylphenols and its quantitative parameters. The results show that the new ant colony optimization algorithm is relatively simple to select variables for quantitative QSAR, and the parameters to be adjusted are few, which is a useful method for variable selection. The correlation coefficient R = 0.994, which is used to model the quantum chemical structure parameters, R = 0.982 in the literature compared to the correlation is better.