| 基于混合量子粒子群优化算法的三维航迹规划 |
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| 引用本文： | 傅阳光,周成平,丁明跃.基于混合量子粒子群优化算法的三维航迹规划[J].宇航学报,2010,31(12):2657-2664. |
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| 作者姓名： | 傅阳光 周成平 丁明跃 |
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| 作者单位： | 1. 华中科技大学图像识别与人工智能研究所，多谱信息处理技术国防科技重点实验室，武汉 430074；2. 华中科技大学生命科学与技术学院，图像信息处理与智能控制教育部重点实验室，武汉 430074 |
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| 摘 要： | 针对粒子群优化算法(PSO)存在的早熟收敛问题，通过将种群的繁殖机制引入量子粒子群优化算法(QPSO)，提出了一种混合量子粒子群优化算法(HQPSO)，将该算法应用于无人飞行器的三维航迹规划。同时，运用统计学方法，通过仿真实验比较了HQPSO算法与QPSO算法以及带动态变化惯性权系数的PSO算法的性能。仿真实验结果表明，HQPSO不但比QPSO和PSO具有更强的全局搜索能力，而且比QPSO和PSO具有更快的收敛速度。
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| 关 键 词： | 无人飞行器 航迹规划 繁殖机制 混合量子粒子群优化 |
| 收稿时间： | 2009-11-12 |
3-D Route Planning Based on Hybrid Quantum-Behaved Particle Swarm Optimization |
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| FU Yang-guang,ZHOU Cheng-ping,DING Ming-yue.3-D Route Planning Based on Hybrid Quantum-Behaved Particle Swarm Optimization[J].Journal of Astronautics,2010,31(12):2657-2664. |
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| Authors: | FU Yang-guang ZHOU Cheng-ping DING Ming-yue |
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| Institution: | 1. Institute for Pattern Recognition and Artificial Intelligence, State Key Laboratory for Multi Spectral Information Processing Technologies, Huazhong University of Science and Technology, Wuhan 430074, China;2. College of Life Science and Technology, “Image Processing and Intelligence Control” Key Laboratory of Education Ministry of China, Huazhong University of Science and Technology, Wuhan 430074, China |
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| Abstract: | In view of the premature convergence problem of particle swarm optimization(PSO),a hybrid quantum-behaved particle swarm optimization algorithm(HQPSO)is presented by introducing the breeding strategy into QPSO in this paper.A method of 3-D route planning for unmanned air vehicle(UAV)is set up on the basis of the proposed HQPSO algorithm.The performance of HQPSO is compared with the QPSO and PSO with inertial weighting coefficients by using a statistical method.Simulation results demonstrate that HQPSO not o... |
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| Keywords: | Unmanned aerial vehicle(UAV) Route planning Breeding strategy Hybrid quantum-behaved particle swarm optimization(HQPSO) |
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