摘要
采用自适应模糊神经网络的方法,以金属离子价电子结构因子、电荷-半径比、适配价轨道数因子等为参数,关联金属离子水解常数.利用减法聚类算法确定模糊神经网络的结构,并结合模糊推理系统进行该网络参数的调整.网络仿真的结果是满意的.自适应模糊神经网络可望成为元素和化合物构效关系研究的辅助手段.
An adaptive fuzzy neural network was applied to study the relationships between the structural parameters of metal ions and their hydrolysis constants pK1 of metal ions, with the parameters of valence electronic structural factor of metal ions（S）, electric charge-radius ratio（Z^2/r）, adaptive valence＇orbit number（w）. Subtractive clustering algorithm is used to confirm the structure of fuzzy neural network, and combined fuzzy inference systems to process regulation of the network parameters. The simulation results are satisfactory. Therefore, the authors can expect that adaptive fuzzy neural network might be used as an effective assistant technique for the investigation of quantitative structure-property relationship（QSPR） of the elements and compounds.
出处
《西南师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2009年第4期42-46,共5页
Journal of Southwest China Normal University(Natural Science Edition)
关键词
人工神经网络
自适应模糊神经网络
金属离子
水解常数
artificial neural network
adaptive fuzzy neural network
metallic ions
hydrolysis constants pK1
