In this study a modified evolution algorithm (MDE) was proposed to improve the searching efficiency of simple differential evolution algorithm (DE). The modified evolution algorithm advanced the performance of global optimization through collecting population information during evolution and at the same time introducing deterministic operation

amending distribution of individuals adaptively. The methods proposed include maintaining population diversity

adding new deterministic simplex searching operation

modifying the probability operation

and others. A typical example indicated good performance of this algorithm. Finally

the MDE has been successfully applied to nonlinear parameter estimation of the model of low temperature SO2 oxidation with Cs-Rb-V sulfuric acid catalyst.