Parameter Identification by MCMC Method for Water Quality Model of Distribution System

摘要：

Parameter identification plays an important role in environmental model application. An integrated method of Markov Chain Monte Carlo simulation (MCMC) and EPANET Multi-Species Extension toolkit was constructed for the parameter identification of water quality model of distribution system, taking bacterial regrowth model with chlorine inhibition as an example. Combined with the prior distribution of the model parameters and water quality observation data, an upgraded algorithm called DRAM was introduced to the MCMC sampling to obtain the posterior parameter distribution. Results indicated that this MCMC method has its special advantages in producing posterior distribution and provides robust means of parameter identification of water distribution system modeling.

关键词： water quality model Bayesian inference Markov Chain Monte Carlo EPANET Multi-Species Eztension parameter identification

作者: Sen Peng Qing Wu Baoyu Zhuang

作者单位: School of Environmental Science and Technology Tianjin University Tianjin,China

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-5

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）