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新的自适应免疫量子粒子群优化算法 被引量：2

New Adaptive Immune Quantum-Behaved Particle Swarm Optimization Algorithm
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摘要 为了克服粒子群优化算法早熟收敛以及粒子在进化过程中缺乏很好的方向指导的问题,算法中采用了量子技术以及免疫机制来提高粒子群的收敛速度和寻优能力,从而获得了一个新的自适应免疫量子粒子群优化算法.仿真试验表明该算法具有较好的性能. In order to escape from premature convergence and lack good direction in particles the evolutionary process,quantum technology and immunologic mechanism were employed to improve the convergence speed and the optimization ability of particle swarm,and a new adaptive immune quantum-behaved particle swarm optimization（NAIQPSO） algorithm was provided.Simulation experiments show that the provided algorithm has better performance.
作者 朱颢东 李红婵
机构地区 郑州轻工业学院计算机与通信工程学院
出处 《微电子学与计算机》 CSCD 北大核心 2011年第3期123-125,129,共4页 Microelectronics & Computer
基金 河南省基础与前沿技术研究计划项目(102300410266) 郑州轻工业学院博士科研基金项目
关键词 粒子群优化 量子技术 免疫机制 particle swarm optimization quantum technology immunologic mechanism
分类号 TP301 [自动化与计算机技术—计算机系统结构]
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参考文献8

  • 1Hamidian D, Seyedpoor S M. Shape optimal design of arch dams using an adaptive neum-fuzzy inference system and improved Particle swarm optimization [J]. Applied Mathematical Modelling, 2010,34(6) : 1574-1585.
  • 2Kuok K K, Harun S, Shamsuddin S M. Particle swarm optimization feedforward neural network for modeling runoff [J]. International Journal of Environmental Science and Technology ,2010, 7(1): 67-78.
  • 3Yannis Marinakis, Magdalene Marinaki. A hybrid particle swarm optimization algorithm for the vehicle routing problem [j]. Engineering Applications of Artificial Intelligence, 2010,23(4):463-472.
  • 4Arya L D, Titare L S, Kothari D P. Improved particle swarm optimization applied to reactive power reserve maximization [J]. International Journal of Electrical Power & Energy Systems, 2010,32(5) : 368-374.
  • 5刘怀亮,苏瑞娟,许若宁,高鹰.协同粒子群优化算法[J].计算机应用,2009,29(11):3068-3073. 被引量：7
  • 6Hamidreza Modares, Alireza Alfi. Parameter identification of chaotic dynamic systems through an improved particle swarm optimization [J]. Expert Systems with Applications, 2010,37(5): 3714-3720.
  • 7Sun Jun, Feng Bin,Xu Wenbo. Particle swarm optimization with particles having quantum behavior [C].//Proe of 2004 Congress on Evolutionary Computation. USA; Piscataway, 2004 : 325 - 330.
  • 8胡江强,郭晨,尹建川,李铁山.分级变异的动态克隆选择算法[J].控制与决策,2007,22(6):608-612. 被引量：11

二级参考文献30

  • 1杜海峰,焦李成,刘若辰.免疫优势克隆算法[J].电子与信息学报,2004,26(12):1918-1924. 被引量：22
  • 2刘怀亮,刘淼.一种混合遗传模拟退火算法及其应用[J].广州大学学报（自然科学版）,2005,4(2):141-145. 被引量：24
  • 3刘怀亮.模拟退火算法及其改进[J].广州大学学报（自然科学版）,2005,4(6):503-506. 被引量：15
  • 4KENNEDY J, EBERHART R C. Particle swarm optimization [ C]// Proceedings of the IEEE Conference on Neural Networks. Washington, DC: IEEE Press, 1995:1942-1948.
  • 5SHI Y, EBERHART R C. A modified particle swarm optimizer [ C]// Proceedings of IEEE International Conference on Evolutionary Computation. Washington, DC: IEEE Press, 1998:69-73.
  • 6SHI Y, EBERHART R C. Empirical study of particle swarm optimization [ C] // Proceedings of IEEE International Congress on Evolutionary Computation. Washington, DC: IEEE Press, 1999: 1945- 1950.
  • 7EBERHART RC, SHI Y. Particle swarm optimization: Developments, applications and resources [ C]//Proceedings of Congress on Evolutionary Computation. Washington, DC: IEEE Press, 2001:81-86.
  • 8CLERC M. The swarm and the queen: Towards a deterministic and adaptive particle swarm optimization [ C]// Proceedings of 1999 Congress on Evolutionary Computation. Washington, DC: IEEE Press, 1999:1951-1957.
  • 9CLERC M, KENNEDY J. The particle swarm: Explosion, stability, and convergence in a multi-dimensional complex space [ J]. IEEE Transactions on Evolutionary Computation, 2002, 6( 1): 58 -73.
  • 10EBERHART R C, SHI Y. Tracking and optimizing dynamic systems with particle swarms [ C]// Proceedings of IEEE Congress on Evolutionary Computation 2001. Washington, DC: IEEE Press, 2001:94 - 97.

共引文献16

同被引文献21

  • 1Kennedy J, Eberhart R. Particle swarm optimization[C]. Proc of IEEE Int Conf on Neural Networks. Perth: IEEE,1995: 1942-1948.
  • 2Van den Bergh E A new locally convergent particle swarm optimizer[C]. Proc of the IEEE Int Conf on Systems, Man and Cybernetics. Tunisia: IEEE, 2002: 94-99.
  • 3Sun J, Feng B, Xu W B. Particle swarm optimization with particles having quantum behavior[C]. Proc of 2004 Congress on Evolutionary Computation. Portland: IEEE, 2004: 325-331.
  • 4Coelho L S. Gaussian quantum-behaved particle swarm optimization approaches for constrained engineeringdesign problems[J]. Expert Systems with Applications, 2010, 37(2): 1676-1683.
  • 5Sun J, Lai C H, Xu W B, et al. A modified quantum- behaved particle swarm optimization [C]. Proc of IEEE Conf on Computational Science. Beijing: IEEE, 2007: 294-301.
  • 6Liu J, Sun J, Xu W B. Improving quantum-behaved particle swarm optimization by simulated annealing[J]. Computational Intelligence and Bioinformatics, 2006, 4115: 130-136.
  • 7Chen D B, Wang J T. An improved group search optimizer with operation of quantum-behaved swarm and its application[J]. Applied Soft Computing, 2012, 12(2): 712-725.
  • 8Sun J, Fang W, Palade V, et al. Quantum-behaved particle swarm optimization with Gaussian distributed local attractor point[J]. Applied Mathematics and Computation, 2011, 218(7): 3763-3775.
  • 9Clerc M, Kennedy J. The particle swarm: Explosion, stability, and convergence in a multi-dimensional complex space[J]. IEEE Trans on Evolutionary Computation, 2002, 6(1): 58-73.
  • 10刘军民,高岳林.混沌粒子群优化算法[J].计算机应用,2008,28(2):322-325. 被引量：68

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二级引证文献14

微电子学与计算机
2011年 第3期

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