摘要
本文通过分析啤酒中酒精在人体体内胃肠(含肝脏)与体液(含血液-)之间的交换机理,分别建立了在短时间内喝酒和长时间喝酒两种情况下,胃肠和体液(含血液)中的酒精含量的微分方程模型。对给出的数据,利用非线性最小二乘数据拟合及高斯-牛顿算法,确定了酒精含量以及酒精从胃肠进入血液的速度系数和酒精从血液渗透出体外的速度系数。继而,对不同喝酒方式下,血液中酒精浓度进行分析:该模型可以预测喝酒后任一时刻血液中的酒精浓度。对于第一问假设大李在第一次检查后半小时喝酒,由于体液中有残留的酒精,故第二次检查时酒精浓度为20.2448毫克/百毫升。
In this paper, we give two differential equations concerning situations, in which a certain amount of alcohol drinks is given in a short time vs. in a long time by analysing the exchange mechanism of alcohol between the stomach (including the liver) and the body fluid (including the blood). Each coefficient is solved, based on given datas by nonlinear least square method and Gauss-Newton's algorithm. As results, we can explain why the density of alcohol in big Li's body is more than 20 milligram / one hundred milliliters in the second inspection.
出处
《工程数学学报》
CSCD
北大核心
2004年第B12期124-130,共7页
Chinese Journal of Engineering Mathematics
关键词
饮洒
微分方程
高斯-牛顿算法
drinking
differential equations
Gauss-Newton's algorithm
