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基于神经网络的电力通信网风险评估方法

DOI: 10.13190/j.jbupt.2014.01.020, PP. 90-93

Keywords: BP神经网络,学习速率,二分法,电力通信网,风险评估

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Abstract:

提出了一种基于神经网络的电力通信网风险评估算法——基于二分法的学习速率自适应BP(backpropagation)神经网络算法.该算法在网络训练过程中使用二分法调整学习速率,使得学习速率在训练过程中不断向最优化方向自动调整.仿真结果表明,收敛速度、误差精度和训练时间等算法性能得到了优化.

References

[1]  Gao Huisheng, Feng Lina. Risk evaluation of the electric power communication network based on compatibility Rough-Fuzzy set[C]//Intelligent Systems and Applications, 2009. 2009: 1-4.
[2]  Zhang Yichuan, Qiao Lifang, Qi Anguo. An evaluation method of wasteland landscape restoration plan based on BP neural network model[J]. Journal of Food Agriculture & Environment, 2012(10): 1093-1095.
[3]  Jing Guolin, Du Wenting, Guo Yingying. Studies on prediction of separation percent in electrodialysis process via BP neural networks and improved BP algorithms[J]. Desalination, 2012(291): 78-93.
[4]  Zhang Feng, Li Pengfeng, Hou Zengguang. sEMG-based continuous estimation of joint angles of human legs by using BP neural network[J]. Neurocomputing, 2012(78): 139-148.
[5]  Jin Juliang, Wei Yiming, Zou Lele, et al. Forewarning of sustainable utilization of regional water resources: a model based on BP neural network and set pair analysis[J]. Natural Hazards, 2012, 62(1): 115-127.
[6]  Zeng Qingtao, Qiu Xuesong, Gao Zhipeng, et al. Adaptive T-S FRBF-based risk assessment method for electric power communication network[J]. Journal of Information and Computational Science, 2012(10): 3063-3070.

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