江苏大学学报（自然科学版）2025，Vol.46Issue(3)：323-329,7.DOI:10.3969/j.issn.1671-7775.2025.03.010
基于等距随机抽样方法的TSMH河流水污染溯源算法
Tracing algorithm of TSMH river water pollution based on equidistant random sampling method
摘要
Abstract
To solve the problem of low computational efficiency caused by the poor selection and acceptance rate of the initial points when the classical Markov chain Monte Carlo(MCMC)algorithm was used to solve the information of river water pollution sources of discharge,discharge time and discharge location,the two-dimensional diffusion model of pollutants was constructed through COMSOL simulation software.The effects of two above aspects on the traceability results of point source water pollution by different algorithms were compared and analyzed,and the two-stage multi-chain Metropolis-Hastings algorithm based on Equidistant random sampling(ERS-TSMH)was proposed.The simulation results show that the traditional MH algorithm and TSMH algorithm are easy to fall into the local optimum or non-convergence during solving,and the acceptance rate of the former is around 20％,while that of the latter reaches nearly 50％.The multi-chain ERS-MH algorithm improves the accuracy of inversion,while it is converged and inefficient after about 10 000 iterations.The multi-chain ERS-TSMH algorithm can guarantee the traceability accuracy,while it is converged after about 5 000 iterations with significantly improved efficiency and high stability and reliability.关键词
水污染溯源/MCMC/COMSOL/等距随机抽样/MH算法/ERS-TSMH算法Key words
water pollution traceability/MCMC/COMSOL/equidistant random sampling/MH algorithm/ERS-TSMH algorithm分类
资源环境引用本文复制引用
鲍煦,朱容松,林锋..基于等距随机抽样方法的TSMH河流水污染溯源算法[J].江苏大学学报（自然科学版）,2025,46(3):323-329,7.基金项目
农业农村部淡水渔业健康养殖重点实验室开放课题(ZJK202204) （ZJK202204）
江苏省六大人才高峰高层次人才计划项目(XYDXX-115) （XYDXX-115）
