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酚类化合物的多元回归分析及神经网络法研究 被引量:2

Study on Phenol Compounds Using Multiple Regression and Neural Network Methods
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摘要 In this paper, the molecular connectivity indices and the electronic charge parameters of forty-eight phenol compounds nave been calculated.and applled for studying the relationship between partition coefficients and structure of phenol compounds.The results demonstrate that the properties of compounds can be described better with selective parameters, and the results obtained by neural network are superior to that by multiplle regression. In this paper, the molecular connectivity indices and the electronic charge parameters of forty-eight phenol compounds nave been calculated.and applled for studying the relationship between partition coefficients and structure of phenol compounds.The results demonstrate that the properties of compounds can be described better with selective parameters, and the results obtained by neural network are superior to that by multiplle regression.
作者 郭明 许禄
出处 《物理化学学报》 SCIE CAS CSCD 北大核心 1996年第11期1027-1030,共4页 Acta Physico-Chimica Sinica
关键词 拓扑指数 酚类化合物 神经网络 多元回归分析 Topological indices, Quantitative structure-activity/property relationship, Phenols
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