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机构地区:[1]中国科学院生态环境研究中心,北京100085 [2]北京联合大学化学工程学院,北京100023
出 处:《中国环境科学》2001年第4期330-334,共5页China Environmental Science
基 金:国家自然科学基金资助项目(29877032)
摘 要:由化学物质毒性效应登录(RTECS)1998年版光盘系统检索获得52种环醚和34种氯代环醚急性毒性数据.应用主成份分析法从11种分子描述符中选择出对急性毒性有明显影响的5种:氯原子数,取代苯环上氢的氯原子数,取代烷基氢的氯原子数,烷基数和氧原子数.通过样本学习集训练并优化神经网络结构、建模分类、预报,对于86个样本,低中和高剧两类毒性,正确分类率达到91%;而对于低、中、高、剧4类毒性,正确分类率达到80%.结果表明,氯代环醚的特殊结构具有很强的致毒作用.Acute toxicity data of 52 cycloethers and 34 polychlorinated cycloethers were collected from a optical disk system of Registry of Toxic Effects of Chemical Substances (RTECS) of 1998 version. By using principal component analysis, 5 kinds having marked influence on acute toxicity were chosen from 11 kinds of molecular structure descriptors; the number of chloro atom, the number of substituted chloro atom in the benzene-cycle, the number of substituted chloro atom in the alkyl, the numbers of alkyl atom and oxygen atom. After learning of above sample sets and neural network structure optimized, the established models were classified, it was predicted: for 86 samples, the correct classifying rate of low-middle and high-severe classes reached 91%; and reached 80% for 4 classes of low, middle, high and severe. Results showed that the special structure of polychlorinated cycloethers possess very high toxicities.
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