基于逆向概率密度函数的一维污染源排放重构

应用逆向概率密度函数进行一维对流扩散方程污染释放过程重构,给出了采用逆向概率与传统优化过程的流程图和主要区别。采用逆向概率密度函数进行污染源重构,其微分方程求解次数等于观测数据量,有效地降低了数值计算量。应用逆向概率密度函数结合优化算法针对一维对流扩散方程中正态波式和矩形波式的污染源排放过程重构的仿真结果显示:对于1～2个污染物正态函数波释放过程,采用一到两个监测点即可准确得辨识出主要参数;3个正态函数波释放过程,采用3个监测点,辨识结果仍有一定误差,可能与模型的非线性特征或释放过程波的相互干扰有关。矩形波释放过程,采用三个监测能准确辨识出所有参数。

Recovering the release history of contaminant based on backward probability density function for the one-dimensional convection diffusion equation

This paper provided a new method to reconstruct the release history of pollution in one-dimensional convection diffusion equation basing on backward probability density function.Flow charts of backward density probability method and traditional optimization method were presented,as well as their differences.The number of solving ADE times is same as the number of samples by using backward density probability function,which improve then numerical efficient greatly.This article made some numerical simulations...