| 基于人工蜂群的 BP 神经网络算法 |
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| 引用本文： | 李卫华,徐涛,李小梨.基于人工蜂群的 BP 神经网络算法[J].计算机系统应用,2012,21(5):195-197,183. |
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| 作者姓名： | 李卫华 徐涛 李小梨 |
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| 作者单位： | 惠州学院计算机科学系,惠州516007 |
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| 基金项目： | 广东高校优秀青年创新人才培育项目（LYM09128）; 惠州学院自然科学青年项目（C210.0306） |
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| 摘 要： | 传统BP神经网络存在容易陷入局部极小点、收敛速度慢等缺点。人工蜂群算法是基于蜜蜂群体的觅食行为而提出的一种新的启发式仿生算法,属于典型的群体智能算法。它为全局优化算法,该算法简单、实现方便、鲁棒性强。针对BP神经网络算法的不足,提出利用人工蜂群算法交叉优化BP网络参数的权值和阈值,实验证明该优化算法确实提高了解的精度,加快了网络收敛速度。
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| 关 键 词： | BP神经网络 人工蜂群 权值 阈值 |
| 收稿时间： | 2011/8/26 0:00:00 |
| 修稿时间： | 2011/10/25 0:00:00 |
BP Neural Network Based on Artificial Bee Colony Algorithm |
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| LI Wei-Hu,XU Tao and LI Xiao-Li.BP Neural Network Based on Artificial Bee Colony Algorithm[J].Computer Systems& Applications,2012,21(5):195-197,183. |
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| Authors: | LI Wei-Hu XU Tao and LI Xiao-Li |
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| Affiliation: | (Computer Science Department,Huizhou University,Huizhou 516007,China) |
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| Abstract: | The traditional BP neural network algorithm has some bugs such that it is easy to fall into local minimum and the slow convergence speed.Artificial Bee Colony Algorithm,which based on foraging behavior of honeybee swarms,is a new heuristic bionic algorithm and a typical kind of swarm intelligence algorithm.It is a global optimum algorithm with many advantages such as simple,convenient and strong robust.In this paper,a new BP neural network based on Artificial Bee Colony Algorithm was proposed to optimize the weight and threshold value of BP neural network.The result shows that the new algorithm improves the precision and expedites the convergence rate. |
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| Keywords: | BP neural network artificial bee colony algorithm weight threshold value |
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