Application of differential evolution algorithm combined with Markov Chain Monte Carlo in parameter optimization of hydrologic model
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Abstract:
Premature conver gence pro blem ex ists in the parameter o ptimization of hydro log ical mo del using the t raditio nal differ2 ential evo lution. In this paper, differ ential evo lutio n adaptive metro po lis algo rithm( DREAM) w as pro po sed, w hich combines the advantag es o f differential ev olut ion algo rithm and Mar ko v Chain M onte Carlo( MCMC) sampler , and applied in the parameter optimizatio n o f CMD23PAR hydro log ic model in the Jialing River Basin. The results show ed that DREAM has the advantag es of self2adaptiv e Metro po lis method, can effectiv ely o vercome the pro blem o f premature converg ence, and is capable to infer the pos2 ter io r distributio n o f model parameters w hich is lack of prior info rmation.
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