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

DOI 被引用文献3件 参考文献3件

書誌事項

タイトル別名
  • PARAMETER IDENTIFICATION OF DISTRIBUTED RUNOFF MODEL USING THE PARTICLE SWARM OPTIMIZATION METHOD

抄録

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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被引用文献 (3)*注記

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参考文献 (3)*注記

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詳細情報 詳細情報について

  • CRID
    1390282680328476928
  • NII論文ID
    130004558008
  • DOI
    10.2208/jscejhe.68.i_523
  • ISSN
    2185467X
  • 本文言語コード
    ja
  • データソース種別
    • JaLC
    • Crossref
    • CiNii Articles
  • 抄録ライセンスフラグ
    使用不可

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