Governed by: Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by: Northwestern Polytechnical University  Chinese Society Aeronautics and Astronautics
Address: Aviation Building,Youyi Campus, Northwestern Polytechnical University
Research on Kernel Extreme Learning Machine Algorithm for Key Node Identification in Aviation Network
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Affiliation:

1.XiJing University,Xi’an;2.Air Traffic Control and Navigation College,AirSForceSEngineeringSUniversity,Xi’an,Shaanxi

Clc Number:

V35 ;[ U8 ]; TP18

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    Abstract:

    In order to improve the safety operation ability of aviation network, a key node identification method based on kernel extreme learning machine is proposed. Firstly, it evaluates the comprehensive importance of nodes based on analytic hierarchy process (AHP). Then, it selects three simple indices and establishes the importance evaluation model based on the mapping relationship between simple indices and comprehensive importance of kernel extreme learning machine. Simulation results show that the proposed method is accurate in evaluation and can overcome the problem of high computation time complexity.

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Niu Junfeng, GAN Xu-sheng, SUN Jing-juan, TU Cong-liang. Research on Kernel Extreme Learning Machine Algorithm for Key Node Identification in Aviation Network[J]. Advances in Aeronautical Science and Engineering,2021,12(1):39-47

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History
  • Received:March 10,2020
  • Revised:May 23,2020
  • Adopted:June 02,2020
  • Online: February 25,2021
  • Published: