Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the ...Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.展开更多
目的探讨SIMCA(soft independent modeling of class analogy)法对肝炎后肝硬化中医证候判识的可行性。方法在对变量进行归一化处理的基础上,用SIMCA法对268例肝炎后肝硬化患者临床症状、体征和生物学指标进行分析,获得相应SIMCA距离并...目的探讨SIMCA(soft independent modeling of class analogy)法对肝炎后肝硬化中医证候判识的可行性。方法在对变量进行归一化处理的基础上,用SIMCA法对268例肝炎后肝硬化患者临床症状、体征和生物学指标进行分析,获得相应SIMCA距离并以之对肝硬化证候进行识别,再运用秩和检验分析误判原因。结果 5种中医证候(肝郁脾虚证、肝肾阴虚证、脾肾阳虚证、湿热内蕴证及瘀热蕴结证)的识别率在最近类中为72.39%,在次近类中为17.91%,总识别率为90.30%。其中,对肝肾阴虚证的识别率最高,总识别率为95.24%。秩和检验分析结果表明,在最近类中,未得到识别者与得到识别者比较,在某些对证候判识起关键作用的症状变量得分方面差异有统计学意义(P<0.05)。结论采用SIMCA法对肝炎后肝硬化中医证候进行判识,与临床实际证候拟合度较高。依据SIMCA法建立证候辨识系统可为中医证候判别提供参考。展开更多
文摘Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.
文摘目的探讨SIMCA(soft independent modeling of class analogy)法对肝炎后肝硬化中医证候判识的可行性。方法在对变量进行归一化处理的基础上,用SIMCA法对268例肝炎后肝硬化患者临床症状、体征和生物学指标进行分析,获得相应SIMCA距离并以之对肝硬化证候进行识别,再运用秩和检验分析误判原因。结果 5种中医证候(肝郁脾虚证、肝肾阴虚证、脾肾阳虚证、湿热内蕴证及瘀热蕴结证)的识别率在最近类中为72.39%,在次近类中为17.91%,总识别率为90.30%。其中,对肝肾阴虚证的识别率最高,总识别率为95.24%。秩和检验分析结果表明,在最近类中,未得到识别者与得到识别者比较,在某些对证候判识起关键作用的症状变量得分方面差异有统计学意义(P<0.05)。结论采用SIMCA法对肝炎后肝硬化中医证候进行判识,与临床实际证候拟合度较高。依据SIMCA法建立证候辨识系统可为中医证候判别提供参考。
