A study of Heuristic Searching approach for dynamic system modeling

A Multi-objects heuristic optimization approach for dynamic system modeling is presented. The optimizing process consists of two searching stages. At first, the optimal regions are explored by GA, which is one of the adaptive search algorithm and effective in many optimal problems. This can lead to compress the searching scope in the optimization effectively. Then the optimal solutions in these regions will be further searched respectively using Heuristic Searching Algorithm(HSA). Heuristic information in HAS is used to find the next searching directions in virtue of the gradient concepts. During the directions searching, evaluations of the results in multi-direction searching are made and the next step will be settle. Several nonlinear functions are used to test the HAS. The results and analysis are discussed. It shows the ability of model in the dynamic system modeling with the features of simplicity and flexibility.