In this paper, considering a scenario in which there are two quality levels of fresh products and introduction of consumer utility function, we studied the optimal ordering and pricing strategies under certain quantit...In this paper, considering a scenario in which there are two quality levels of fresh products and introduction of consumer utility function, we studied the optimal ordering and pricing strategies under certain quantity. Our results showed that, facing the two quality levels of fresh products, retailers would not benefit from sales of lower quality of fresh products with the deterministic demand. In the pursuit of profit maximization, the initial order quantity is smaller than the potential demand for market.展开更多
应用便携式近红外光谱仪采集320份生鲜猪肉在近红外光谱中波区的光谱信息,采用不同优化方法建立猪肉胆固醇预测模型,并对异常样品的剔除及组合预处理方法对模型性能的改善进行了分析。研究表明:通过对异常值的二次剔除,并使用SG一阶导数...应用便携式近红外光谱仪采集320份生鲜猪肉在近红外光谱中波区的光谱信息,采用不同优化方法建立猪肉胆固醇预测模型,并对异常样品的剔除及组合预处理方法对模型性能的改善进行了分析。研究表明:通过对异常值的二次剔除,并使用SG一阶导数(savitzky-golay first derivative,SG 1st D)、SG平滑(savitzky-golay smoothing,SGS)和正交信号校正(OSC)的组合预处理方法,可获得最佳生鲜猪肉胆固醇预测模型,其参数如下:校正集相关系数(Rc)=0.9137,校正标准差(standard error of calibration,SEC)=2.5607,验证集相关系数(Rp)=0.656 7,预测标准差(standard error of prediction,SEP)=4.985 5,主因子数(principal factor,PF)=4,范围误差比(ratio of performance to standard deviation,RPD)=2.5032,相对预测标准差(relative standard error of prediction,RSEP)=8.625 4%,SEP/SEC=1.946 8,说明模型在近红外光谱中波区对猪肉胆固醇的分辨能力和预测准确度较好,通过向校正集中补充代表性样品可使模型稳健性进一步改善。对检验集样品预测值(prediction value,PV)与参比值(reference value,RV)的t检验显示二者之间无显著性差异(p>0.05),检验集样品总体预测准确率为62.5%,其中50~70mg·(100g)-1区段的局部预测准确率达到91.7%,可以用于生鲜猪肉胆固醇浓度的在线快速初步定量分析。该研究将便携式近红外光谱用于在近红外中波区对生鲜猪肉及肉制品中胆固醇浓度的分析和检测,通过进一步的研究和改进,可将其应用于产品的原料分级、品质和过程控制及市售产品的抽检等。展开更多
文摘In this paper, considering a scenario in which there are two quality levels of fresh products and introduction of consumer utility function, we studied the optimal ordering and pricing strategies under certain quantity. Our results showed that, facing the two quality levels of fresh products, retailers would not benefit from sales of lower quality of fresh products with the deterministic demand. In the pursuit of profit maximization, the initial order quantity is smaller than the potential demand for market.
文摘应用便携式近红外光谱仪采集320份生鲜猪肉在近红外光谱中波区的光谱信息,采用不同优化方法建立猪肉胆固醇预测模型,并对异常样品的剔除及组合预处理方法对模型性能的改善进行了分析。研究表明:通过对异常值的二次剔除,并使用SG一阶导数(savitzky-golay first derivative,SG 1st D)、SG平滑(savitzky-golay smoothing,SGS)和正交信号校正(OSC)的组合预处理方法,可获得最佳生鲜猪肉胆固醇预测模型,其参数如下:校正集相关系数(Rc)=0.9137,校正标准差(standard error of calibration,SEC)=2.5607,验证集相关系数(Rp)=0.656 7,预测标准差(standard error of prediction,SEP)=4.985 5,主因子数(principal factor,PF)=4,范围误差比(ratio of performance to standard deviation,RPD)=2.5032,相对预测标准差(relative standard error of prediction,RSEP)=8.625 4%,SEP/SEC=1.946 8,说明模型在近红外光谱中波区对猪肉胆固醇的分辨能力和预测准确度较好,通过向校正集中补充代表性样品可使模型稳健性进一步改善。对检验集样品预测值(prediction value,PV)与参比值(reference value,RV)的t检验显示二者之间无显著性差异(p>0.05),检验集样品总体预测准确率为62.5%,其中50~70mg·(100g)-1区段的局部预测准确率达到91.7%,可以用于生鲜猪肉胆固醇浓度的在线快速初步定量分析。该研究将便携式近红外光谱用于在近红外中波区对生鲜猪肉及肉制品中胆固醇浓度的分析和检测,通过进一步的研究和改进,可将其应用于产品的原料分级、品质和过程控制及市售产品的抽检等。