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无网格法在地下水水位预测中的应用

焦玉玲1,刘金英2,杨天行3,鲍新华4   

  1. 1.吉林大学 应用技术学院,长春 130022;2.吉林大学 数学学院,长春 130026;3.吉林大学 地球探测科学与技术学院,长春 130026;4.吉林大学 环境与资源学院,长春 130026
  • 收稿日期:2006-06-29 修回日期:1900-01-01 出版日期:2007-05-26 发布日期:2007-05-26
  • 通讯作者: 焦玉玲

Application of Meshless Method in Groundwater Level Forecast

JIAO Yu-ling1, LIU Jin-ying2,YANG Tian-xing3,BAO Xin-hua4   

  1. 1.College of Applied Technology, Jilin University, Changchun 130022,China;2.College of Mathematics,Jilin University, Changchun 130026,China;3.College of GeoExploration Science and Technology, Jilin University, Changchun 130026,China;4.College of Environment and Resources, Jilin University, Changchun 130026,China
  • Received:2006-06-29 Revised:1900-01-01 Online:2007-05-26 Published:2007-05-26
  • Contact: JIAO Yu-ling

摘要: 基于移动最小二乘理论的无网格法是近几年来兴起的一种新的数值计算方法,与有限元法相比,它的主要优点在于无需单元信息,只需节点信息。用无网格法构造了场函数,包括基函数和权函数的选取,形函数及其导数的计算。根据鞍山市首山区水文地质条件,建立了求解双层渗流二维平面系统的数学模型,详细推导了模型求解的无网格方程。应用已识别的参数,用无网格法对该数学模型进行了求解, 并对该区的地下水水位进行了预测,预测的水位与实际水位变化规律基本一致。

关键词: 无网格法, 权函数, 水位预测, 鞍山市首山区

Abstract: MLS-based meshless method is a new numerical method in near few years and has such advantages as only requirement of node information of nodes rather than element over finite element method.Meshless method is applied to construct the field functions including the selection of base function and weight function and the shape function and to compute the derivatives of these both functions. On the basis of hydrogeological conditions in Shoushan region,Anshan City,Liaoning Province, a mathmatical model to solve the two-dimensional plane groundwater flow system with double-layer structure has been set up and the meshless equation to solve the mathematical model bas also been educed.The mathmatics model has been solved using meshless method based on the caliberated parameter.The forecasted groundwater level in the region with this method is consistent with the observed change.

Key words: meshless method, weight function, water level forecast, Shoushan region in Anshan City

中图分类号: 

  • P641.2
[1] 刘博, 肖长来, 梁秀娟. SOM-RBF神经网络模型在地下水位预测中的应用应用[J]. 吉林大学学报(地球科学版), 2015, 45(1): 225-231.
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