| 具有时间因子的粒子群优化算法 |
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| 引用本文： | 周喜虎,高兴宝.具有时间因子的粒子群优化算法[J].纺织高校基础科学学报,2011,24(2):303-308. |
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| 作者姓名： | 周喜虎 高兴宝 |
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| 作者单位： | 陕西师范大学数学与信息科学学院,陕西 西安,710062 |
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| 基金项目： | 国家自然科学基金资助项目(60671063,10902062) |
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| 摘 要： | 粒子群算法是一种基于群体智能的随机搜索优化方法,能够有效的优化各类函数.提出了具有时间因子的粒子群优化算法,其目的在于克服基本粒子群算法的早熟与收敛速度慢等缺点.数值试验表明,具有时间因子的粒子群优化算法收敛速度更快,运算达到的精度更高,运行更为稳定,并能有效克服局部极值.
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| 关 键 词： | 粒子群 进化算法 时间因子 智能计算 |
Particle swarm optimization with time factor |
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| ZHOU Xi-hu,GAO Xing-bao.Particle swarm optimization with time factor[J].Basic Sciences Journal of Textile Universities,2011,24(2):303-308. |
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| Authors: | ZHOU Xi-hu GAO Xing-bao |
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| Affiliation: | ZHOU Xi-hu,GAO Xing-bao(College of Mathematics and Information Science,Shaanxi Normal University,Xi'an 710062,China) |
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| Abstract: | Particle swarm optimization algorithm is random search optimization algorithm on the basis of group intelligence,which can effectively optimize the various functions.To overcome the premature and slow convergence,an improved particle swarm optimization is presented by inducing a time factor to adjust the convergence rate.Numerical experiments show that the improved algorithm not only has faster convergence,more accurate and stable,but also avert the local extreme values effectively. |
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| Keywords: | particle swarm evolution algorithms time factor computational intelligence |
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