PARAMETER IDENTIFICATION OF DISTRIBUTED RUNOFF MODEL USING THE PARTICLE SWARM OPTIMIZATION METHOD

DOI 3 Citations 3 References
  • KOTSUKI Shunji
    Department of Urban Management, Graduate School of Engineering, Kyoto University, Japan
  • TANAKA Kenji
    Disaster Prevention Research Institute, Kyoto University, Japan
  • KOJIRI Toshiharu
    Disaster Prevention Research Institute, Kyoto University, Japan
  • HAMAGUCHI Toshio
    Disaster Prevention Research Institute, Kyoto University, Japan

Bibliographic Information

Other Title
  • 群知能最適化手法を用いた分布型流出モデルのパラメーター同定

Abstract

In this paper, the particle swarm optimization (PSO) is applied into automatic parameter calibration process of a distributed runoff model. As distributed runoff models require long simulation time compared with general optimization problems, the number of particles and repeat computation times should be selected property. We conducted sensitivity experiments for the number of particles and found that the PSO has to be applied in following conditions: i) to set the number of particles more than 100 in the case of calibrating about five parameters, ii) to conduct repeat computations about 25 times. Analyzed river discharge using identified parameters shows good agreement with the observed one.

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Details 詳細情報について

  • CRID
    1390282680328476928
  • NII Article ID
    130004558008
  • DOI
    10.2208/jscejhe.68.i_523
  • ISSN
    2185467X
  • Text Lang
    ja
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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