文献类型：期刊文章

作　　者：崔秀君[1] 张卓勇[2] Peterde B Harrington[3] 任玉林[4]

机构地区：[1]东北师范大学化学学院,长春130024 [2]首都师范大学化学系三维信息获取与应用教育部重点实验室,北京100037 [3]俄亥俄大学化学系,athens457012979 [4]吉林大学化学学院,长春130023

出　　处：《高等学校化学学报》

基　　金：北京市教育委员会科学技术发展项目 (批准号 :KM2 0 0 3 10 0 2 810 5 )资助

年　　份：2004

卷　　号：25

期　　号：7

起止页码：1251-1253

语　　种：中文

收录情况：AJ、BDHX、BDHX2000、CAS、CSCD、CSCD2011_2012、EI、IC、JST、RCCSE、RSC、SCIE、SCOPUS、WOS、ZGKJHX、核心刊

摘　　要：Temperature-constrained cascade correlation networks(TCCCNs) were applied to the identification of the powder pharmaceutical samples of metronidazole based on near infrared(NIR) diffuse reflectance spectra. This work focused on the comparison of performances of the uni-output TCCCN(Uni-TCCCN) to multi-output TCCCN(Multi-TCCCN) by using near infrared diffuse reflectance spectra of metronidazole. The TCCCN models were verified with independent prediction samples by using the "cross-validation" method. The networks were used to discriminate qualified, un-qualified and counterfeit metronidazole pharmaceutical powders. The results showed that multiple outputs network generally worked better than the single output networks. With proper network parameters the pharmaceutical powders can be classified at a rate of 100% in this work. Also, the effects of neural network parameters including number of candidate nodes, type of transfer functions(linear, sigmoid functions and temperature-constrained sigmoid function, respectively) on classification were discussed.

关 键 词：甲硝唑 质量控制  温度限制串联相关神经网络  近红外反射光谱法

分 类 号：R979.8]