Population Migration Algorithm Description Method and Application Based on Unified Framework of Swarm Intelligence

نویسندگان

  • Yongquan Zhou
  • Weiwei Zhang
  • Aijia Ouyang
چکیده

Population migration algorithm (PMA) is proposed in recent years, it’s a new search algorithm for global optimization that mainly simulates population transition with economics and dispersion with population pressure increment, the former encourages the algorithm to search in a region with good solutions, the latter avoids getting stuck in a local optimum to a certain degree. So far, and there was no unified framework to describe this algorithm. This paper describes the population migration algorithm based on a unified framework of swarm intelligence, as well as combination with chaos map, a chaos population migration and PMA for training RBF neural network algorithm are proposed. Finally, two numerical experiment examples results show that the PMA algorithm is effective and accuracy.

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عنوان ژورنال:
  • JNW

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2010