改进的微粒群算法模拟动物的群体觅食行为

Extending the Particle Swarm Optimization to Model Animal Foraging Behaviour

以改进的微粒群算法为工具,试图建立能更加准确反映实际动物觅食行为的模型,并对其进行仿真研究。从食物的分布、微粒对周围同伴的感知范围及微粒的综合感知能力等方面对原有的模型进行了改进。仿真结果表明改进了的模型能够更好地表现动物的群体觅食行为,并且更加真实自然地反应生态现象。

This paper proposes an extending particle swarm algorithm to model animal foraging behaviours. Improvements on the previous model is made through food distribution, scope of perception of particles to others and integrated perceptibility of particle to food. Emulational results prove＇that the animal group-foraging behaviors could be carried out in a better way from those aspects, and that ecology phenomenon can be natrually reflected.