| 基于蚁群算法的模糊神经网络垂直切换算法 |
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| 引用本文： | 郭强,车玉洁,阎跃鹏.基于蚁群算法的模糊神经网络垂直切换算法[J].电子技术,2014(3):5-9. |
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| 作者姓名： | 郭强 车玉洁 阎跃鹏 |
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| 作者单位： | 山东财经大学管理科学与工程学院山东济南 |
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| 摘 要： | 提出了基于蚁群算法(ACO)优化的模糊神经网络垂直切换算法ACO-FNN,综合考虑了信号强度、移动速度、可用带宽等因素进行模糊神经网络处理,并采用蚁群算法进行优化,调整隶属度函数的参数。仿真结果表明,该算法能够在减少乒乓效应的基础上更好的保证用户的服务质量QOS。
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| 关 键 词： | 异构网络 网络选择 模糊神经网络 蚁群算法 |
An ACO-Based Fuzzy Neuron Network Access Selection Algorithm in Heterogeneous Wireless Networks |
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| Guo Qiang Che Yujie Yan Yuepeng.An ACO-Based Fuzzy Neuron Network Access Selection Algorithm in Heterogeneous Wireless Networks[J].Electronic Technology,2014(3):5-9. |
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| Authors: | Guo Qiang Che Yujie Yan Yuepeng |
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| Affiliation: | Guo Qiang Che Yujie Yan Yuepeng (Institute of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, Shangdong) |
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| Abstract: | An ant colony optimization （ACO）-fuzzy neural network access selection algorithm optimized on the basis of AOC algorithm is put forward, which takes radio signal strength, terminal moving speed and network bandwidth into consideration to process fuzzy neural network processing module. The specialty of the algorithm is using ACO to optimize and adjust the parameters of membership function. The simulation results show that the proposed algorithm can decrease the packet dropping probability, reduce the happening times of Ping-Pong effect and decrease the blockin~ probability on the consideration of ~uaranteeing the QoS for users. |
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| Keywords: | heterogeneous wireless network access selection fuzzy neural network ant colony optimization |
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