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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....
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...
This paper presents a hybrid learning approach for dynamic system modelling and prediction using neural networks. The model learning is divided into two parts. One is to select the global region and the other is to find the goal value. A heuristic learning algorithm (HLA) is discussed, which is effective in the real-time dynamic modelling and control. The hybrid model is applied to the on-line prediction...
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