Computer Science ›› 2019, Vol. 46 ›› Issue (12): 108-113.doi: 10.11896/jsjkx.181102207
• Network & Communication • Previous Articles Next Articles
ZHANG Jie1, BAI Guang-wei1, SHA Xin-lei1, ZHAO Wen-tian1, SHEN Hang1,2
CLC Number:
[1]Cisco Visual Networking Index:Forecast and Methodology 2016-2021[EB/OL].https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vnicomplete-white-paper-c11-481360.html.[2]SUNDARESAN K.5G:An Evolution towards a Revolution[C]// Proceedings of ACM International Conference on Mobile Computing and Networking.New Delhi,India,2018:659-659.[3]IMRAN A,ZOHA A.Challenges in 5G:How to Empower SON with Big Data for Enabling 5G [J].IEEE Network,2014,28(6):27-33.[4]NIU Z,WU Y,GONG J,et al.Cell Zooming For Cost-Efficient Green Cellular Networks [J].IEEE Communications Magazine,2010,48(11):74-79.[5]XU F,LIN Y,HUANG J,et al.Big Data Driven Mobile Traffic Understanding and Forecasting:A Time Series Approach [J].IEEE Transactions on Services Computing,2016,9(5):796-805.[6]SHU Y,YU M,LIU J,et al.Wireless Traffic Modeling and Pre- diction Using Seasonal ARIMA Models[C]//Proceedings of IEEE International Conference on Communications.Anchorage:IEEE,2003:1675-1679.[7]LI R,ZHAO Z,ZHENG J,et al.The learning and prediction of application-level traffic data in cellular networks [J].IEEE Transactions on Wireless Communications,2017,16(6):3899-3912.[8]ZHANG C,PAUL P.Long-term mobile traffic forecasting using deep spatio-temporal neural networks[C]//Proceedings of ACM International Symposium on Mobile Ad Hoc Networking and Computing.Angeles:ACM,2018:231-240.[9]OLIVEIRA T P,BARBAR J S,SOARES A S.Computer Network Traffic Prediction:A Comparison between Traditional and Deep Learning Neural Networks [J].International Journal of Big Data Intelligence,2016,3(1):28-37.[10]NAREJO S,PASERO E.An Application of Internet Traffic Prediction with Deep Neural Network [J].Multidisciplinary Approaches to Neural Computing,2018,69(1):139-149.[11]HUANG C W,CHIANG C T,LI Q.A Study of Deep Learning Networks on Mobile Traffic Forecasting[C]//Proceedings of IEEE Personal,Indoor,and Mobile Radio Communications.Montreal:IEEE,2017:1-6.[12]LI R,ZHAO Z,ZHOU X,et al.The Prediction Analysis of Cellular Radio Access Network Traffic:From Entropy Theory to Networking Practice [J].IEEE Communications Magazine,2014,52(6):234-240.[13]FU R,ZHANG Z,LI L.Using LSTM and GRU neural network methods for traffic flow prediction[C]//Proceedings of IEEE Youth Academic Annual Conference of Chinese Association of Automation.Wuhan:IEEE Press,2016:324-328.[14]YU F,KOLTUN V.Multi-scale context aggregation by dilated convolutions[C]//Proceedings of International Conference on Learning Representations.San Juan:ICLR,2016.[15]HE K,ZHANG X,REN S,et al.Deep residual learning for ima- ge recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Nevada:IEEE,2016:770-778.[16]ZHOU F Y,JIN L P,DONG J.Review of Convolutional Neural Network[J].Chinese Journal of Computers,2017,40(6):1229-1251.[17]IOFFE S,SZEGEDY C.Batch normalization:accelerating deep network training by reducing internal covariate shift[C]//Proceedings of International Conference on International Conference on Machine Learning.Lille:ACM,2015:448-456.[18]GIANNI B,MARCO D N,ROBERTO L,et al.A multi-source dataset of urban life in the city of Milan and the Province of Trentino[J].Scientific Data,2015,2:150055. |
[1] | ZHANG Ying-tao, ZHANG Jie, ZHANG Rui, ZHANG Wen-qiang. Photorealistic Style Transfer Guided by Global Information [J]. Computer Science, 2022, 49(7): 100-105. |
[2] | WANG Shan, XU Chu-yi, SHI Chun-xiang, ZHANG Ying. Study on Cloud Classification Method of Satellite Cloud Images Based on CNN-LSTM [J]. Computer Science, 2022, 49(6A): 675-679. |
[3] | GAO Zhi-yu, WANG Tian-jing, WANG Yue, SHEN Hang, BAI Guang-wei. Traffic Prediction Method for 5G Network Based on Generative Adversarial Network [J]. Computer Science, 2022, 49(4): 321-328. |
[4] | LI Si-quan, WAN Yong-jing, JIANG Cui-ling. Multiple Fundamental Frequency Estimation Algorithm Based on Generative Adversarial Networks for Image Removal [J]. Computer Science, 2022, 49(3): 179-184. |
[5] | LIU Yang, LI Fan-zhang. Fiber Bundle Meta-learning Algorithm Based on Variational Bayes [J]. Computer Science, 2022, 49(3): 225-231. |
[6] | HU Yan-li, TONG Tan-qian, ZHANG Xiao-yu, PENG Juan. Self-attention-based BGRU and CNN for Sentiment Analysis [J]. Computer Science, 2022, 49(1): 252-258. |
[7] | SONG Yuan-long, LYU Guang-hong, WANG Gui-zhi, JIA Wu-cai. SDN Traffic Prediction Based on Graph Convolutional Network [J]. Computer Science, 2021, 48(6A): 392-397. |
[8] | LI Shan, XU Xin-zheng. Parallel Pruning from Two Aspects for VGG16 Optimization [J]. Computer Science, 2021, 48(6): 227-233. |
[9] | ZHAN Rui, LEI Yin-jie, CHEN Xun-min, YE Shu-han. Street Scene Change Detection Based on Multiple Difference Features Network [J]. Computer Science, 2021, 48(2): 142-147. |
[10] | CHEN Hao-nan, LEI Yin-jie, WANG Hao. Lightweight Lane Detection Model Based on Row-column Decoupled Sampling [J]. Computer Science, 2021, 48(11A): 416-419. |
[11] | ZENG De-ze, LI Yue-peng, ZHAO Yu-yang, GU Lin. Reinforcement Learning Based Dynamic Basestation Orchestration for High Energy Efficiency [J]. Computer Science, 2021, 48(11): 363-371. |
[12] | WANG Xin-ping, XIA Chun-ming, YAN Jian-jun. Sign Language Recognition Based on Image-interpreted Mechanomyography and Convolution Neural Network [J]. Computer Science, 2021, 48(11): 242-249. |
[13] | XIAO Shi-long, WU Di, TANG Chao-chen, SHEN Xian-hao, ZHANG De-yu. Control Application of Wolf Group Optimization Convolutional Neural Network in Ship Virtual Manufacturing [J]. Computer Science, 2021, 48(10): 135-139. |
[14] | WANG Jiao-jin, JIAN Mu-wei, LIU Xiang-yu, LIN Pei-guang, GEN Lei-lei, CUI Chao-ran, YIN Yi-long. Video Saliency Detection Based on 3D Full ConvLSTM Neural Network [J]. Computer Science, 2020, 47(8): 195-201. |
[15] | CAO Su-e, YANG Ze-min. Prediction of Wireless Network Traffic Based on Clustering Analysis and Optimized Support Vector Machine [J]. Computer Science, 2020, 47(8): 319-322. |
|