Abstract:

This paper describes a simplex-differential evolution hybrid algorithm to analyze experimental water quality data of river stream, and estimates water quality parameters for a 1-D river under longitudinal dispersion and a 2-D river under transverse diffusion. This algorithm combines the features of simplex method and differential evolution method: the former has a strong local search ability and fast convergence but higher dependence on the selection of initial parameters; the latter has an strong global search ability and fewer controlled parameters but weak local search ability. The combined algorithm has advantages in both random searching and deterministic calculation, and well balances the local against global search ability. Numerical experiments show that this new algorithm is of fast convergence and cost saving in analysis of experiment data of water quality and estimation of water quality parameters of river stream, and thus it has a good application potential.