In order to differentiate regions, varieties, and parts of tobacco leaves, two pattern recognition methods through pattern classification modeling were developed based on the comprehensive information of ultraviolet-v...In order to differentiate regions, varieties, and parts of tobacco leaves, two pattern recognition methods through pattern classification modeling were developed based on the comprehensive information of ultraviolet-visible spectroscopy （UV-VIS） by employing one-way analysis of variance （ANOVA1） and wave range random combination （WRRC） technology from MATLAB. This proposed classification method has never been reported previously and the instrument and operation for this method is much more convenient and efficient than previous reported classification methods. The result of this paper demonstrated that the spectral features extracted by ANOVAI and WRRC methods could be used to differentiate tobacco leaves with different patterns. The ANOVAI method had a training recognition rate range of 75.00-87.50%,4 and a validation recognition rate range of 57.14-100%. The WRRC method had a training recognition rate range of 75.00-94.12% and a validation recognition rate range of 66.67-100%. The ANOVAI method is more convenient and efficient in model developing, while the WRRC method utilizes fewer model variables and is more robust.展开更多
采用差紫外谱法研究了新型芳酰胺-吖啶分子钳(1～7)对苯胺、苯二胺(邻,间,对)等中性分子的识别性能.测定了结合常数(K_a)和自由能变化(△G°),结果表明,所有的分子钳受体与所考察的客体分子均形成1∶1型超分子配合物.识别作用的主...采用差紫外谱法研究了新型芳酰胺-吖啶分子钳(1～7)对苯胺、苯二胺(邻,间,对)等中性分子的识别性能.测定了结合常数(K_a)和自由能变化(△G°),结果表明,所有的分子钳受体与所考察的客体分子均形成1∶1型超分子配合物.识别作用的主要推动力为多重氢键、van der Waals等的协同作用.主客体间尺寸/形状匹配、几何互补等因素对识别性能均有重要的影响.利用核磁氢谱与计算机模拟作为辅助手段对主要的实验结果与现象进行了解释.展开更多
文摘In order to differentiate regions, varieties, and parts of tobacco leaves, two pattern recognition methods through pattern classification modeling were developed based on the comprehensive information of ultraviolet-visible spectroscopy （UV-VIS） by employing one-way analysis of variance （ANOVA1） and wave range random combination （WRRC） technology from MATLAB. This proposed classification method has never been reported previously and the instrument and operation for this method is much more convenient and efficient than previous reported classification methods. The result of this paper demonstrated that the spectral features extracted by ANOVAI and WRRC methods could be used to differentiate tobacco leaves with different patterns. The ANOVAI method had a training recognition rate range of 75.00-87.50%,4 and a validation recognition rate range of 57.14-100%. The WRRC method had a training recognition rate range of 75.00-94.12% and a validation recognition rate range of 66.67-100%. The ANOVAI method is more convenient and efficient in model developing, while the WRRC method utilizes fewer model variables and is more robust.
文摘采用差紫外谱法研究了新型芳酰胺-吖啶分子钳(1～7)对苯胺、苯二胺(邻,间,对)等中性分子的识别性能.测定了结合常数(K_a)和自由能变化(△G°),结果表明,所有的分子钳受体与所考察的客体分子均形成1∶1型超分子配合物.识别作用的主要推动力为多重氢键、van der Waals等的协同作用.主客体间尺寸/形状匹配、几何互补等因素对识别性能均有重要的影响.利用核磁氢谱与计算机模拟作为辅助手段对主要的实验结果与现象进行了解释.
