Parameters identification for water environmental system based on Bayesian inference

To overcome the difficulty in the identification of parameters of the water environmental system caused by the limited observation data with noise,Bayesian algorithm was constructed for the parameters identification of the water environmental system,taking one dimensional water quality model as example.Combined with the prior distribution of the model parameters and water quality observation data,joint posterior probability function which stands for the distribution characters was obtained by Bayes′ Theorem.Markov chain monte carlo simulation(MCMC) was taken to sample the posterior distribution to get the marginal posterior probability function of the parameters,and the statistical quantities such as the mathematic expectation were calculated.The computational results indicate that parameters estimation by Bayesian method and MCMC sampling has a high precision.The algorithm′s construction is direct and simple,which solves the identification problem of the water environmental system successfully.