摘要
运用函数连接型神经网络研究 3 8种取代芳烃化合物的分子结构—毒性的定量构效关系 (QSAR) ,计算结果与MLR计算结果比较 ,前者比后者好。与实验结果的线性拟合相关系数 ,FLN所得结果为 0 9561～ 0 9996,MLR所得结果为 0 869～ 0 965。
Systematic studies were made on the applications of the Functional\|Link Net (FLN), a novel single\|layer neural network, without hidden neurons, to the relationship between the Na\|+\|K\++ adenosine triphosphatase activities and the chemical structures of substituted aromatic compounds. The nonlinearity of original input patterns is enhanced, and the generalized δ\|learning rule is used in FLN. By comparing the FLN with multiple linear regression models (MLR), it was found that the former behaves better than the latter. The correlation coefficients, 0 9561～0 9996, of the results obtained by FLN is better than those of the results obtained by MLR, 0 869～0 965.
出处
《计算机与应用化学》
CAS
CSCD
2000年第1期18-18,共1页
Computers and Applied Chemistry
基金
国家自然科学基金! ( 2 97750 0 1 )资助项目
关键词
取代芳烃
分子结构
QSAR
神经网络
Na-K-ATP酶
Computer chemistry
Functional\|link net
Na\++\|K\++\|ATPase activity
Quantitative structure\|activity relationship(QSAR)
Substituted aromatic compounds
