Page 104 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 4 – AI and machine learning solutions in 5G and future networks
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ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 4




          [3]   Wang  Y.,  Gong  B.,  Gong  M.  Research  on  the   [15]  Hagberg  A.,    Schult  D.,    Swart  P.  NetworkX
               Trusted  Energy-Saving  Transmission  of  Data        Tutorial.  2011.
               Center Network. China Communications, 2016.
                                                               [16]  Chuan  W.  W.,  Zhang  B.  M.  A  GRAPHIC
          [4]   Kamiyama  N.  Network  Topology  Design              DATABASE  BASED  NETWORK  TOPOLOGY
               Using Data Envelopment Analysis[C]// IEEE             AND  ITS  APPLICATION[J].  Power  System
               Globecom-ieee  Global  Telecommunications             Technology, 2002.
               Conference. IEEE, 2017.
                                                               [17]  Chen  L.  W.,  Martin  N.,  Cabrera  C.,  et  al.
          [5]   Liu Z.,  Zou Z. Analysis of network topology         Communication        network      topology
               and deployment mode of 5G wireless access             determination:  US,  US20110188409  A1[P].
               network[J]. Computer Communications, 2020,            2011.
               160.
                                                               [18]  Wang  H.,    Chen  Y.  Network  topology
          [6]   Singh J P. THE ROLE OF AI, ML, AND IOT IN            description and visualization[J]. IEEE, 2010.
               DIGITAL  TRANSFORMATION  IN  2019[J].  PC       [19]  O'Brien  P.  S.  Optimizing  hand-off  neighbor
               Quest, 2019, 32(1):18-19.
                                                                     lists  for  improved  system  performance[J].
          [7]   Liu  Z.,  Yubo  M  U.,  Zhang  Y.  Overview  of      2004.
               network  artifical  intelligence  requirements   [20]  Sánchez-Torrubia  M.  G.,  Torres-Blanc  C.,
               and    applications.   Telecommunications             Cubillo S. Design Of A Fuzzy Inference System
               Network Technology, 2018.
                                                                     For Automatic DFS & BFS Algorithm Learning
          [8]   Weytjens  H.,    Lohmann  E.,    Kleinsteuber  M.    Assessment [M].  2015.
               Cash  flow  prediction:  MLP  and  LSTM         [21]  Vijay  I.,    Garg  K.  Algorithm  DFS(S):  begin.
               compared  to  ARIMA  and  Prophet[J].                 2003.
               Electronic Commerce Research, 2019(1).
                                                               [22]  Yang C., Ma J., Yao Z., et al. Method for routing
          [9]   Trappey C  V., Wu H Y. An evaluation of the          mobile node in wireless mesh network and a
               time-varying   extended   logistic,   simple          communication system thereof [J]. 2012.
               logistic, and Gompertz models for forecasting
               short   product    lifecycles[J].   Advanced    [23]  Wang W., Yang W., Yang C., et al. Method For
               Engineering        Informatics,      2008,            Routing  Mobile  Node  In  Wireless  Mesh
               22(4):421-430.                                        Network  And  A  Communication  System
                                                                     Thereof [J]. 2008.
          [10]  Greff K.,  Srivastava R K. , J Koutník, et al. LSTM:
               A Search Space Odyssey[J]. IEEE Transactions    [24]  Jinsong  Gui,  Kai  Zhou.  Flexible  Adjustments
               on    Neural   Networks     and   Learning            Between  Energy  and  Capacity  for  Topology
               Systems","pubMedId":"27411231, 2017.                  Control in Heterogeneous Wireless Multi-hop
                                                                     Networks. Central South University,2016.
          [11]  Do We Really Need Deep Learning Models for
               Time Series Forecasting?, 2021.                 [25]  Rui Ma, Xianghui Cao, Shuai Zhang, Lu Liu, Yu
          [12]  Gers  F.  A.,  Eck  D.,  Schmidhuber  J.  Applying   Cheng  and  Changyin  Sun.  A  DBN-based
               LSTM  to  Time  Series  Predictable  through          Independent  Set  Learning  Algorithm  for
               Time-Window      Approaches[J].   Springer,           Capacity Optimization in Wireless Networks.
               Berlin, Heidelberg, 2001.                             Southeast University,2018.

          [13]  Moustapha A. I.,  Selmic R. R . Wireless Sensor   [26]  Brandon  Heller,  Srini  Seetharaman,  Priya
               Network Modeling Using Modified Recurrent             Mahadevan,  Yiannis  Yiakoumis,  Puneet
               Neural  Networks:  Application  to  Fault             Sharma, Sujata Banerjee and Nick McKeown.
               Detection[J].   IEEE    Transactions    on            ElasticTree:  Saving  Energy  in  Data  Center
               Instrumentation  &  Measurement,  2008,               Networks. Stanford University. 2010.
               57(5):981-988.                                  [27]  Bryan Perozzi, Rami Al-Rfou, Steven Skiena.
          [14]  Sang  C.,  MD  Pierro.  Improving  trading           DeepWalk:  Online  Learning  of  Social
               technical  analysis  with  TensorFlow  Long           Representations.  Stony  Brook  University
               Short-Term Memory (LSTM) Neural Network               Department of Computer Science. 2014.
               - ScienceDirect[J]. The Journal of Finance and
               Data Science, 2019, 5(1):1-11.





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