...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Grey systems: theory and application >Geodetic deformation forecasting based on multi-variable grey prediction model and regression model
【24h】

Geodetic deformation forecasting based on multi-variable grey prediction model and regression model

机译：基于多变量灰色预测模型和回归模型的大地变形预测

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Purpose - The purpose of this paper is to examine the effectiveness of the multivariable grey prediction model in deformation forecasting. Design/methodology/approach - Deformation in a dam can be seen because of many factors but without any doubt, the most influential factor is the water level. In this study, the deformation level of a point in the Keban Dam crest has been tried to be forecasted depending on the water level by the multivariable grey model GM(1,N). Regression analysis was used to test the accuracy of the prediction results obtained using the grey prediction model. Findings - The results show that there is a great consistency between the grey prediction values and the actual values, and that the GM(1,N) produces more reliable results than the regression analysis. Based on the results, it can be concluded that the GM(1,N) is a very reliable estimation model for limited data conditions. Originality/value - Different from the other studies in the literature, this study investigates deformation in a dam subject to the water level in the dam reservoir. The main contribution of the study to the literature is to suggest a relatively new procedure for estimating the deformation in the dams based on the water level.
机译：目的-本文的目的是检验多变量灰色预测模型在变形预测中的有效性。设计/方法/方法-由于许多因素，可以看到大坝的变形，但毫无疑问，影响最大的因素是水位。在这项研究中，尝试通过多变量灰色模型GM（1，N）根据水位预测Keban坝顶点的变形水平。回归分析用于测试使用灰色预测模型获得的预测结果的准确性。结果-结果表明，灰色预测值与实际值之间存在很大的一致性，并且GM（1，N）的结果比回归分析更可靠。根据结果​​，可以得出结论：GM（1，N）是用于有限数据条件的非常可靠的估计模型。原创性/价值-与文献中的其他研究不同，本研究调查的是受水库水位影响的水坝变形。该研究对文献的主要贡献是提出了一个相对较新的程序，用于基于水位估算大坝的变形。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号