浏览全部资源
扫码关注微信
[ "李佳(1991- ),女,国网吉林省电力有限公司信息通信公司工程师,主要从事通信网络运行工作" ]
[ "丛犁(1984- ),女,博士,国网吉林省电力有限公司信息通信公司高级工程师,主要从事通信网运行管理工作" ]
[ "姜华(1985- ),男,国网吉林省电力有限公司信息通信公司工程师,主要从事通信网调度管理工作" ]
[ "胡杨(1988- ),男,国网吉林省电力有限公司信息通信公司工程师,主要从事通信网调度工作" ]
[ "徐梦(1993- ),女,国网吉林省电力有限公司信息通信公司助理工程师,主要从事通信网络检修工作" ]
网络出版日期:2020-10,
纸质出版日期:2020-10-20
移动端阅览
李佳, 丛犁, 姜华, 等. 基于DBN-Softmax的电力通信网络带宽预测[J]. 电信科学, 2020,36(10):153-158.
Jia LI, Li CONG, Hua JIANG, et al. Bandwidth prediction of power communication network based on DBN-Softmax[J]. Telecommunications science, 2020, 36(10): 153-158.
李佳, 丛犁, 姜华, 等. 基于DBN-Softmax的电力通信网络带宽预测[J]. 电信科学, 2020,36(10):153-158. DOI: 10.11959/j.issn.1000-0801.2020155.
Jia LI, Li CONG, Hua JIANG, et al. Bandwidth prediction of power communication network based on DBN-Softmax[J]. Telecommunications science, 2020, 36(10): 153-158. DOI: 10.11959/j.issn.1000-0801.2020155.
随着电力通信网的变化,电力通信网承载业务数据呈指数级增长,对电力通信网的处理能力提出了更高要求。为保障通信网的服务质量,针对目前网络带宽分配不合理现象,提出基于深度置信的电力通信网带宽预测算法,该算法通过由限制玻尔兹曼机构成的深度置信网络获取能够完美表达网络带宽的特征,实现对电力通信网规划阶段带宽的合理预测。实验结果表明,与传统神经网络算法相比,所提算法在预测精度和稳健性方面更具有优势,可以提高电力通信网的承载能力,为电力系统的安全稳定运行提供有力的保障。
With the change of the power communication network
the data of the bearer service of the power communication network has increased exponentially
which puts higher requirements on the processing capability of the power communication network.In order to guarantee the service quality of communication network
aiming at the current unreasonable distribution of network bandwidth
a bandwidth prediction algorithm based on deep confidence for power communication network was proposed.The deep confidence network formed by the Boltzmann machine was used to obtain the characteristics that could perfectly express the network bandwidth
and the reasonable prediction of the bandwidth of the power communication network planning stage was realized.The implementation results show that the proposed algorithm is more accurate and robust than neural network.It has the advantage of improving the carrying capacity of the power communication network and providing a powerful guarantee for the safe and stable operation of the power system.
黄志才 . 电力通信网可靠性研究 [J ] . 中国新通信 , 2015 , 17 ( 18 ): 28 - 29 .
HUANG Z C . Research on reliability of electric power communication network [J ] . China New Communication , 2015 , 17 ( 18 ): 28 - 29 .
张俊宇 . 电力通信网可靠性研究 [J ] . 通讯世界 , 2016 , 15 ( 13 ):140.
ZHANG J Y . Research on reliability of electric power communication network [J ] . Communication World , 2016 , 15 ( 13 ):140.
郝治理 , 刘春生 , 周青松 . 用于干扰对消的稀疏约束卡尔曼滤波算法 [J ] . 空军工程大学学报 , 2020 ( 2 ): 13 - 16 .
HAO Z L , LIU C S , ZHOU Q S . Sparsely constrained Kalman filter algorithm for interference cancellation [J ] . Journal of Air Force Engineering University , 2020 ( 2 ): 13 - 16 .
涂锦 , 冷正兴 , 刘丁毅 . 基于EMD和神经网络的非线性时间序列预测方法 [J ] . 统计与决策 , 2020 ( 8 ): 21 - 26 .
TU J , LENG Z X , LIU D Y . Nonlinear time series prediction method based on EMD and neural network [J ] . Statistics and Decision , 2020 ( 8 ): 21 - 26 .
ZOU X Y . Deep learning学习笔记整理系列 [EB ] . 2013 .
ZOU X Y . Deep learning study notes sorting series [EB ] . 2013 .
CHEN H , MURRAY A F . Continuous restricted Boltzmann machine with an implementable training algorithm [J ] . IEE Process.-Vision.Image Signal Process , 2003 , 150 ( 3 ): 153 - 158 .
景亚鹏 . 基于深度学习的欺骗性垃圾信息识别研究 [D ] . 上海:华东师范大学 , 2014 : 25 - 26 .
JING Y P . Research on deceptive spam recognition based on deep learning [D ] . Shanghai:East China Normal University , 2014 : 25 - 26 .
张春霞 , 姬楠楠 , 王冠伟 . 受限波尔兹曼机 [J ] . 工程数学学报 , 2015 ( 2 ): 159 - 173 .
ZHANG C X , JI N N , WANG G W . Restricted boltzmann [J ] . Journal of Engineering Mathematics , 2015 ( 2 ): 159 - 173 .
尹宝才 , 王文通 , 王立春 . 深度学习研究综述 [J ] . 北京工业大学学报 , 2015 ( 1 ): 48 - 59 .
YIN B C , WANG W T , WANG L C . Summary of deep learning research [J ] . Journal of Beijing University of Technology , 2015 ( 1 ): 48 - 59 .
0
浏览量
162
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构