• DocumentCode
    2484248
  • Title

    The application of particle swarm optimization algorithms to estimation of aquifer parameters from data of pumping test

  • Author

    Hongfei, Zhou ; Jianqing, Guo

  • Author_Institution
    Xinjiang Inst. of Ecology & Geogr., Acad. Sinica, Urumqi, China
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 2 2010
  • Firstpage
    945
  • Lastpage
    950
  • Abstract
    With the application of article swarm optimization algorithms (PSO), the function optimization problem of analyzing pumping test data in aquifer to estimate such parameters as transmissivity and storage coefficient was to be solved. With the different number of particles and the initial guessed values of transmissivity, the numerical experiments were conducted to explore the effect of these factors on the convergence of PSO algorithm . The results show : 1) that PSO algorithm may be effectively applied to solve the function optimization problem of analyzing pumping test data in aquifer to estimate transmissivity and storage coefficient , 2..that the convergence of PSO algorithm and the computation time are influenced by the number of particles, and the fewer iterations are needed in computation with the larger number of particles , 3) that the ranges of initial guessed values of transmissivity may also bring some effect on the convergence of PSO algorithm and the computation time, the larger the ranges are , the more number of iterations and the longer computation time are needed to guaranteed the convergence of PSO algorithm. Compared with other current methods, PSO method is of such advantages as that the principle is easy to understand and the procedure of computation is simple to realized.
  • Keywords
    groundwater; parameter estimation; particle swarm optimisation; pumps; PSO method; aquifer parameter estimation; particle swarm optimization; pumping test; Algorithm design and analysis; Biological system modeling; Convergence; Equations; Mathematical model; Optimization; Particle swarm optimization; aquifer parameters; convergence of algorithm; key parameters of algorithm; particle swarm optimization(PSO); pumping test data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Convergence Information Technology (ICCIT), 2010 5th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-8567-3
  • Electronic_ISBN
    978-89-88678-30-5
  • Type

    conf

  • DOI
    10.1109/ICCIT.2010.5711196
  • Filename
    5711196