| 多氯酚QSAR数值模型比较研究 |
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| 引用本文： | 王桂莲,白乃彬.多氯酚QSAR数值模型比较研究[J].环境科学学报,1996,16(2):190-194. |
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| 作者姓名： | 王桂莲 白乃彬 |
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| 作者单位： | 中国科学院生态环境研究中心 |
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| 摘 要： | 应用多元线性回归分析和新近发展起来的人工神经网络方法进行了一类重要环境污染物多氯酚的定量构效关系研究，并用所建立的模型进行毒性预报，计算值与实验值的比较表明，前的相关系数约为０．９２，后的相关系数约为０．９９．后的百分误差地明显小于前，后的预报能力略好于前，中还讨论了后优于前的的原因。
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| 关 键 词： | 多氯酚 QSAR 神经网络 多元回归分析 |
| 收稿时间： | 1994/11/9 0:00:00 |
QSAR MODELS FOR CHLOROPHENOL |
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| Wang Guilian and Bai Naibin.QSAR MODELS FOR CHLOROPHENOL[J].Acta Scientiae Circumstantiae,1996,16(2):190-194. |
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| Authors: | Wang Guilian and Bai Naibin |
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| Institution: | Research Center for Eco-Environmental Sciences, Chinese Academy of Scinese, Beijing 100085 and Research Center for Eco-Environmental Sciences, Chinese Academy of Scinese, Beijing 100085 |
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| Abstract: | Two quantitative structure-activity relationship (QSAR) models for chlorophenol are constructed by use of multivariate linear regresion analysis and artificial neural networks. They are used to predict toxicities of the chlorophenol not included in the training set. By comparing the calculated values and the experiment results, it was concluded that artificial neural networks approach for QSAR study of environmental pollutants is better than multivariate linear regression analysis. |
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| Keywords: | chlorophenol QSAR neural networks |
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