• DocumentCode
    256716
  • Title

    A New PSO Algorithm LM Operator Embedded in for Solving Systems of Nonlinear Equations

  • Author

    Guang Xu ; Guocai Hu ; Junfeng Chen

  • Author_Institution
    Dept. of Airborne Vehicle Eng., Naval Aeronaut. & Aetronautical Univ., Yantai, China
  • Volume
    2
  • fYear
    2014
  • fDate
    26-27 Aug. 2014
  • Firstpage
    142
  • Lastpage
    145
  • Abstract
    Aimed at the widespread significance of solving high dimensional nonlinear equations in practical engineering, for the faultiness of classical methods about initial value sensitivity, systems of nonlinear equations are transformed to function optimization, combining with the advantages of PSO, SA and LM, a new method is proposed, in which, according to the idea of SA, LM operator is embedded in PSO. Besides, adaptive damp factor is led into LM operator, which improves efficiency of convergence. The method takes full advantages of above three methods, solving the problems such as initial value sensitivity of LM and falling into local extreme value of PSO. Experimental results of comparing with other methods show that the proposed method has reliable convergence probability and high computation rate, which is an effective method of dealing with systems of nonlinear equations in practical engineering.
  • Keywords
    nonlinear equations; particle swarm optimisation; statistical analysis; LM operator; Levenberg-Marquadt operator; PSO algorithm; adaptive damp factor; convergence probability; function optimization; initial value sensitivity; nonlinear equations; particle swarm optimization; Algorithm design and analysis; Convergence; Damping; Genetic algorithms; Nonlinear equations; Optimization; Reliability; LM optimization; PSO; SA; embedded operator; systems of nonlinear equations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2014 Sixth International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4956-4
  • Type

    conf

  • DOI
    10.1109/IHMSC.2014.137
  • Filename
    6911468