| 人工神经网络及分子拓扑参数在酚类有机物QSBR研究中的应用 |
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| 引用本文： | 瞿福平,杨义燕,冯旭东,戴猷元.人工神经网络及分子拓扑参数在酚类有机物QSBR研究中的应用[J].环境科学,1999,20(5):16-19. |
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| 作者姓名： | 瞿福平 杨义燕 冯旭东 戴猷元 |
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| 作者单位： | 清华大学化学工程系 |
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| 基金项目： | 国家“九五”科技攻关课题 |
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| 摘 要： | 利用分子拓扑参数作为输入参数，探索了人工神经网络对２７种酚类有机物的定量结构－生物降解性能关系（ＱＳＢＲ）。结果表明，将人工神经网络运用于有机物的生物降解性能建模是可行的。所建模型预测结果和文献数据十分接近，预测能力优于已有文献报道，且能够较好区分同分异构体。
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| 关 键 词： | 人工神经网络 QSBR 酚类有机物 分子拓扑 |
| 收稿时间： | 1998/12/7 0:00:00 |
An Application of Artificial Neural Networks and Molecular Topological Index for the QSBR of Phenolic Organics |
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| Qu Fuping,Yang Yiyan,Feng Xudong and Dai Youyuan.An Application of Artificial Neural Networks and Molecular Topological Index for the QSBR of Phenolic Organics[J].Chinese Journal of Environmental Science,1999,20(5):16-19. |
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| Authors: | Qu Fuping Yang Yiyan Feng Xudong and Dai Youyuan |
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| Institution: | Department of Chemical Engineering, Tsinghua University, Beijing 100084 China;Department of Chemical Engineering, Tsinghua University, Beijing 100084 China;Department of Chemical Engineering, Tsinghua University, Beijing 100084 China;Department of Chemical Engineering, Tsinghua University, Beijing 100084 China |
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| Abstract: | A quantitative structurebiodegradability relationships (QSBR)type model using artificial neural networks (ANN)was established for the 27 phenolic compounds, in which molecular topological index are calculated and taken as the input parameters. The results show that the model developed can make a better agreement between predicted and observed values for the biodegradability of the tested compounds than ever before. |
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| Keywords: | ANN QSBR phenolic organics |
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