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A hybrid heuristic searching approach for dynamic system modeling is presented. The paper suggests that the model consists of two function parts - GAs and heuristic random searching algorithm (HRSA). GA is one of the adaptive search algorithms which are able to find global solutions or regions in optimal problem. This character is helpful for reducing the searching range in many optimal problems. Based on this foundation, the solutions within these separate regions will be located further by HRSA. Heuristic information is used to form the next possible searching directions in virtue of the gradient concepts. It reduces the computing time of modeling and speed up the identification of the nonlinear dynamic system. Sereral functions are used to test. The results and analysis are discussed. It shows the ability of model in the dynamic system modeling with the features of simplicity and flexibility.