| 自主式粒子群优化模型研究 |
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| 引用本文： | 申元霞.自主式粒子群优化模型研究[J].重庆邮电学院学报(自然科学版),2009,21(4):507-511. |
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| 作者姓名： | 申元霞 |
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| 作者单位： | 西南交通大学信息科学与技术学院;重庆邮电大学计算机科学与技术研究所;重庆文理学院计算机学院; |
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| 基金项目： | 国家自然科学基金(60773113);;重庆市自然科学基金(2008BA2017) |
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| 摘 要： | 建立了自主式粒子群优化模型,进一步完善了经典粒子群优化算法的学习机制,提高了粒子学习的自主性。在该模型的基础上,针对自主选择共享信息问题,提出了一种学习榜样自主获取的粒子群优化算法,该算法粒子依据自身的内在特征合理地选择学习榜样,充分地利用了进化过程中产生的信息,有效抑制共享信息的流速。对常用单峰多峰基准函数进行了测试,验证了该算法的效率和优越性。
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| 关 键 词： | 自主式学习 粒子群 认知水平 个体差异 |
Study on self-regulated model of particle swarm optimization |
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| SHEN Yuan-xia,.Study on self-regulated model of particle swarm optimization[J].Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition),2009,21(4):507-511. |
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| Authors: | SHEN Yuan-xia |
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| Institution: | 1.School of Information Science and Technology;Southwest Jiaotong University;Chengdu 600031;P.R.China;2.Institute of Computer Science and Technology;Chongqing University of Posts and Telecommunications;Chongqing 400065;3.Department of Computer Science;Chongqing University of Arts and Sciences;Chongqing 402160;P.R.China |
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| Abstract: | The self-regulated model of particle swarm optimization was built to further consummate the learning mechanism of the classical particle swarm optimization and enhance the self-learning ability of the particle.The particle swarm optimization with self-regulated acquisition of the example was developed to actively select sharing information in the self-regulated model of particle swarm optimization.The particle can select example by the inherent factors,which makes full use of the beneficial information gene... |
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| Keywords: | self-regulated learning particle swarm cognitive level individual difference |
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