邱颖豫, 陈功平, 殷志锋. 改进的粒子群算法在多用户检测中的应用[J]. 信阳师范学院学报(自然科学版), 2008, 21(3): 455-457.
引用本文: 邱颖豫, 陈功平, 殷志锋. 改进的粒子群算法在多用户检测中的应用[J]. 信阳师范学院学报(自然科学版), 2008, 21(3): 455-457.
QIU Ying-yu, CHEN Gong-ping, YIN Zhi-feng. Improved Particle Swarm Optimization and its Application to Multiuser Detection[J]. Journal of Xinyang Normal University (Natural Science Edition), 2008, 21(3): 455-457.
Citation: QIU Ying-yu, CHEN Gong-ping, YIN Zhi-feng. Improved Particle Swarm Optimization and its Application to Multiuser Detection[J]. Journal of Xinyang Normal University (Natural Science Edition), 2008, 21(3): 455-457.

改进的粒子群算法在多用户检测中的应用

Improved Particle Swarm Optimization and its Application to Multiuser Detection

  • 摘要: 群智能是一种基于对分散的、自组织的集群行为的模拟而得到的一种人工智能技术,粒子群算法和蚁群算法是其中的典型代表.本文通过分析两种算法的缺陷,提出了一种粒子群算法和蚁群算法相结合的混合算法,扩大了搜索空间,降低了搜索陷入局部极小的概率.

     

    Abstract: Swarm intelligence(SI)is an artificial intelligence technique based on the study of collective behavior in decentralized,self-organized systems.Particle swarm optimization(PSO)and ant colony optimization(ACO)are good examples.A hybrid algorithm is obtained by the combination of PSO with ACO under analysis of the imperfections of them.The new algorithm extends the space of searching and reduces the probability of sinking into local minimum.

     

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