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ANN-ACCO手法による数値モデルの検定に関する研究


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Title: ANN-ACCO手法による数値モデルの検定に関する研究
Other Titles: Model Calibration using ANN-ACCO Optimization Method
Authors: 西田, 渉 / Solomatine, Dimitri P. / 野口, 正人
Authors (alternative): Nishida, Wataru / Solomatine, Dimitri P. / Noguchi, Masato
Issue Date: Nov-2007
Publisher: 長崎大学工学部
Citation: 長崎大学工学部研究報告 Vol.37(69) p.27-32, 2007
Abstract: In order to properly simulate the natural phenomena using numerical model, model parameters have to be estimated by an appropriate manner. Here, new approach using ACCO and artificial neural network is proposed for the calibration of numerical simulation model. ANN works as an error estimator in this proposed model. From the comparison of results with ACCO, although the number of function evaluation time is larger than that of ACCO, it is shown that the optimization by ANN-ACCO is reasonably carried out with better accuracy and stability. Model calibration was also successfully established by ANN-ACCO, then the some degree of its applicability to model calibrations were shown.
Keywords: global optimization / adaptive cluster covering method / artificial neural network / model calibration
URI: http://hdl.handle.net/10069/9461
Relational Links: http://www.lb.nagasaki-u.ac.jp/reports/kougaku/preview.php?id=51
Type: Departmental Bulletin Paper
Text Version: publisher
Appears in Collections:Volume 37, No. 69

Citable URI : http://hdl.handle.net/10069/9461

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