In the study of mathematical ecology, the modeling of natural ecosystem, which is the foundation of further research, is of great importance. The Superposition Procedure is of highly value in practice and has extensive applicable area. Owing to the complexity of natural ecological systems, the implementation of Superposition Procedure by using classical parameter estimation methods is difficult and can seldom obtain satisfactory results. In this paper, after analyzing characteristics of ecological models, it is proposed that the global optimization method can be applied to estimate the parameters of ecological models. Because the specific information of objective functions is not needed when applying global optimization methods , this kind of optimization method is rather robust and therefore is suitable to estimate the parameters of nonlinear models, whose responses are very sensitive to their parameters. Besides the possibility of the implementation and techniques, some simulate results are also presented . A new global optimization algorithm - Random Bisection Algorithm - is presented in this paper as well.
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