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基于人工蜂群算法的群体动画研究与应用 被引量:7

Research and Implementation of Group Animation Based on Particle Swarm Optimization
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摘要 对群体行为的仿真一直是动画研究领域的重点,传统的群体动画制作手段工作量大,制作出的效果不能满足人们的需求,同时如何表现出个体运动的独立性以及群体运动的整体性是群体行为仿真的难点所在。为解决上述问题,将人工蜂群算法应用于群体行为仿真中。首先对人工蜂群算法原理分析,然后将人工蜂群算法的智能性应用于群体动画中,即使用了人工蜂群算法的思想,又针对不同群体行为进行了修改,从而产生了一种新的快速的制作群体动画的方法。仿真结果表明,人工蜂群算法能够真实模拟群体行为,为设计提供了依据。 Simulating group behavior is always a hot issue in computer animation. The traditional means of group animation costs lots and can not meet people' s needs, and the difficulty is how to show the independence of individual and the wholeness of group. This paper applied Artificial Bee Colony Algorithm(ABC) to simulate the behavior of group behavior. It analyzed ABC firstly, and then used the group intelligence of ABC to the group animation. It not only used the idea of ABC, but also modified ABC according to the different group behavior. Then it created a new method to generate group animation quickly. The simulation experiments proof that it can simulate group behavior in an actual way.
作者 于君 刘弘
出处 《计算机仿真》 CSCD 北大核心 2012年第1期180-183,230,共5页 Computer Simulation
基金 山东省教育厅科技发展计划项目(J08LJ14)
关键词 微粒群算法 群体动画 人工蜂群算法 Particle swarm optimization algorithm (PSO) Group animation Artificial bee colony algorithm(ABC)
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