| QSAR结合人工神经网络预测磺酰脲类除草活性 |
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| 引用本文： | 何琴,郭丽丽.QSAR结合人工神经网络预测磺酰脲类除草活性[J].许昌师专学报,2012(2):87-90. |
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| 作者姓名： | 何琴 郭丽丽 |
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| 作者单位： | 许昌学院化学化工学院,河南许昌461000 |
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| 基金项目： | 基金项目：河南雀教育厅自然科学研究计划项目（20098150023） |
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| 摘 要： | 采用误差反传前向人工神经网络模型研究了18种磺酰脲类化合物的结构与除草活性之间的关系.以18种磺酰脲类化合物的量子化学参数作为输入,除草活性作为输出,构建网络模型,取得了较好的预测结果.网络的自相容能力和交叉检验结果良好.该方法还可作为QSAR研究及对有机化合物其他性质进行预测的一种有效手段.
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| 关 键 词： | 磺酰脲类 定量结构-活性关系 人工神经网络 除草活性 |
Prediction for the Herbicidal Activities of Sulfonylurea Compounds with QSAR-ANN |
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| HE Qin,GUO Li-li.Prediction for the Herbicidal Activities of Sulfonylurea Compounds with QSAR-ANN[J].Journal of Xuchang Teachers College(Social Science Edition),2012(2):87-90. |
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| Authors: | HE Qin GUO Li-li |
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| Institution: | ( College of Chemistry and Chemical Engineering, Xuchang University, Xuchang 461000, China) |
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| Abstract: | The relationship between the structures of 18 sulfonylurea compounds and their herbicidal activi- ties was studied by using the neural network based on the back propagation algorithm. The prediction results were examined by a self-consistency test and a cross-validation test. The self-consistency test and the cross-validation test obtained good results when using the quantum chemical parameters about structure as the inputs of the neural network and their herbicidal activities as the outputs. This method may be helpful for QSAR＇ s study and may he effective in predicting other important properties of organics. |
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| Keywords: | sulfonylurea compound quantitative structure-activity relationship artificial neural network herbicidal activity |
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