中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/50586
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 80990/80990 (100%)
造访人次 : 41639868      在线人数 : 1241
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/50586


    题名: Development of an artificial neural network model for determination of longitudinal and transverse dispersivities in a convergent flow tracer test
    作者: Shieh,HY;Chen,JS;Lin,CN;Wang,WK;Liu,CW
    贡献者: 應用地質研究所
    关键词: SCALE-DEPENDENT DISPERSION;AQUIFER PARAMETERS;FIELD;SYSTEMS
    日期: 2010
    上传时间: 2012-03-27 17:37:21 (UTC+8)
    出版者: 國立中央大學
    摘要: The convergent flow tracer test is an efficient method for determining dispersivity in field, but the traditional curve-fitting method for the estimation of dispersivity from a convergent flow tracer test is quite time-consuming. In this study, we present a model to improve the evaluation of longitudinal and transverse dispersivities from a convergent flow tracer test which couples a back-propagation neural network (BPN) model with a two-dimensional convergent flow tracer transport model. The prediction errors for the training and validation data show that with the effective porosity fitting model, the scale-dependent longitudinal dispersivity fitting model, and the scale-dependent transverse dispersivity fitting model, we can obtain satisfactory prediction accuracy with much less computational time. The applicable ranges of parameters are: The Peclet number is between 0.5 and 100, the effective porosity is between 0.05 and 0.5 and the scale-dependent transverse dispersivity is between 0.01 and 10 m. One set of hypothetical data and one set of field data are used to demonstrate the robustness and accuracy of the back-propagation neural network fitting model (BPNFM). The results demonstrate that BPNFM has the advantage of significantly saving the computational time and giving more accurate transport parameter values. The developed BPNFM is an effective tool for fast and accurate evaluation of the longitudinal and transverse dispersivities for a field convergent flow tracer test. (c) 2010 Elsevier B.V. All rights reserved.
    關聯: JOURNAL OF HYDROLOGY
    显示于类别:[應用地質研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML744检视/开启


    在NCUIR中所有的数据项都受到原著作权保护.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明