在干涉式光纤陀螺组成的捷联惯性导航系统中,光纤陀螺启动过程中温变效应导致的漂移项是导航误差的主要误差源,已成为限制高精度光纤陀螺系统性能进一步提升的关键因素。通过对光纤陀螺启动过程中温变效应的理论分析与建模,提出了一种...在干涉式光纤陀螺组成的捷联惯性导航系统中,光纤陀螺启动过程中温变效应导致的漂移项是导航误差的主要误差源,已成为限制高精度光纤陀螺系统性能进一步提升的关键因素。通过对光纤陀螺启动过程中温变效应的理论分析与建模,提出了一种基于查表补偿的光纤陀螺启动温变效应误差抑制法和误差评价法。实验结果表明,该抑制方法可使-40^+60℃环境下光纤陀螺漂移概率误差从0.02~0.50(°)/h降至0.01(°)/h以下,对应导航系统的导航圆概率误差从1.4~35 n mile/h降至0.8 n mile/h以下,有效抑制了光纤陀螺启动温变效应误差,提升了系统性能。展开更多
Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacoki...Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacokinetics parameters,nonlinear mixed effects model(NONMEM),has the abuses of tedious work and plenty of man-made jamming factors.The Elman feedback neural network was built.The relationships between the patients’plasma concentration of remifentanil and time,patient’age,gender,lean body mass,height,body surface area,sampling time,total dose,and injection rate through network training were obtained to predict the plasma concentration of remifentanil,and after that,it was compared with the results of NONMEM algorithm.In conclusion,the average error of Elman network is 6.34%,while that of NONMEM is 18.99%.The absolute average error of Elman network is 27.07%,while that of NONMEM is 38.09%.The experimental results indicate that Elman neural network could predict the plasma concentration of remifentanil rapidly and stably,with high accuracy and low error.For the characteristics of simple principle and fast computing speed,this method is suitable to data analysis of short-acting anesthesia drug population pharmacokinetic and pharmacodynamics.展开更多
文摘在干涉式光纤陀螺组成的捷联惯性导航系统中,光纤陀螺启动过程中温变效应导致的漂移项是导航误差的主要误差源,已成为限制高精度光纤陀螺系统性能进一步提升的关键因素。通过对光纤陀螺启动过程中温变效应的理论分析与建模,提出了一种基于查表补偿的光纤陀螺启动温变效应误差抑制法和误差评价法。实验结果表明,该抑制方法可使-40^+60℃环境下光纤陀螺漂移概率误差从0.02~0.50(°)/h降至0.01(°)/h以下,对应导航系统的导航圆概率误差从1.4~35 n mile/h降至0.8 n mile/h以下,有效抑制了光纤陀螺启动温变效应误差,提升了系统性能。
基金Project(31200748)supported by the National Natural Science Foundation of China
文摘Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacokinetics parameters,nonlinear mixed effects model(NONMEM),has the abuses of tedious work and plenty of man-made jamming factors.The Elman feedback neural network was built.The relationships between the patients’plasma concentration of remifentanil and time,patient’age,gender,lean body mass,height,body surface area,sampling time,total dose,and injection rate through network training were obtained to predict the plasma concentration of remifentanil,and after that,it was compared with the results of NONMEM algorithm.In conclusion,the average error of Elman network is 6.34%,while that of NONMEM is 18.99%.The absolute average error of Elman network is 27.07%,while that of NONMEM is 38.09%.The experimental results indicate that Elman neural network could predict the plasma concentration of remifentanil rapidly and stably,with high accuracy and low error.For the characteristics of simple principle and fast computing speed,this method is suitable to data analysis of short-acting anesthesia drug population pharmacokinetic and pharmacodynamics.
