Parameter Identification of Complicated Environmental Model Using the Soft-computing Approach
软计算技术在环境复杂模型参数识别中的应用研究

In order to study the performance and efficiency of soft-computing technology in application to parameter identification of complicated environmental model,a case study was presented,which was an application of water quality simulation in the Miyun Reservoir using WASP model.Parameter analysis indicated that there were many low sensitivity parameters in WASP model and several groups of parameters were correlative apparently.For analyzing effects of sensitivity and correlativity,four numerical experiments were designed.Resulted indicated that global searching method could solve global optimization well and also was an efficient step to acquire auxiliary information of parameters,And MCMC method could sample posterior distributions of parameters effectively;moreover,sampling series could converge to the posterior distributions of parameters eventually.Case study indicated that it was efficient and practicable for the soft-computing approach presented by the paper to identify parameters of complicated model.