首页> 外文会议>IEEE Symposium Series on Computational Intelligence >QDDS: A Novel Quantum Swarm Algorithm Inspired by a Double Dirac Delta Potential
【24h】

QDDS: A Novel Quantum Swarm Algorithm Inspired by a Double Dirac Delta Potential

机译:QDDS:受双Dirac Delta势启发的新型量子群算法

获取原文

摘要

In this paper a novel Quantum Double Delta Swarm (QDDS) algorithm modeled after the mechanism of convergence to the center of attractive potential field generated within a single well in a double Dirac delta well setup has been put forward and the preliminaries discussed. Theoretical foundations and experimental illustrations have been incorporated to provide a first basis for further development, specifically in refinement of solutions and applicability to problems in high dimensional spaces. Simulations are carried out over varying dimensionality on four benchmark functions, viz. Rosenbrock, Rastrigrin, Griewank and Sphere as well as the multidimensional Finite Impulse Response (FIR) Filter design problem with different population sizes. Test results illustrate the algorithm yields superior results to some related reports in the literature while reinforcing the need of substantial future work to deliver near-optimal results consistently, especially if dimensionality scales up.
机译:本文提出了一种新颖的量子双三角群算法(QDDS),该算法以双狄拉克三角洲双井设置中的单井内产生的吸引势场的中心收敛机制为模型,并进行了初步讨论。结合了理论基础和实验插图,为进一步开发提供了第一个基础,特别是在改进解决方案和对高维空间中的问题的适用性方面。在四个基准函数上,即在变化的维数上进行模拟。 Rosenbrock,Rastrigrin,Griewank和Sphere以及具有不同人口规模的多维有限冲激响应(FIR)滤波器设计问题。测试结果表明,该算法比文献中的一些相关报告产生了更好的结果,同时也增强了对未来进行大量工作以一致地提供接近最佳结果的需求,尤其是在维数扩大的情况下。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号