首页> 外文期刊>International journal of applied mechanics >Application of Principal Component Analysis and Cluster Analysis in Regional Flood Frequency Analysis: A Case Study in New South Wales, Australia
【24h】

Application of Principal Component Analysis and Cluster Analysis in Regional Flood Frequency Analysis: A Case Study in New South Wales, Australia

机译:主成分分析及集群分析在区域洪水频率分析中的应用 - 以澳大利亚新南威尔士州为例

获取原文
获取原文并翻译 | 示例
           

摘要

This paper examines the applicability of principal component analysis (PCA) and cluster analysis in regional flood frequency analysis. A total of 88 sites in New South Wales, Australia are adopted. Quantile regression technique (QRT) is integrated with the PCA to estimate the flood quantiles. A total of eight catchment characteristics are selected as predictor variables. A leave-one-out validation is applied to determine the efficiency of the developed statistical models using an ensemble of evaluation diagnostics. It is found that the PCA with QRT model does not perform well, whereas cluster/group formed with smaller sized catchments performs better (with a median relative error values ranging from 22% to 37%) than other clusters/groups. No linkage is found between the degree of heterogeneity in the clusters/groups and precision of flood quantile prediction by the multiple linear regression technique.
机译:本文研究了主成分分析(PCA)和集群分析在区域洪水频率分析中的适用性。 澳大利亚新南威尔士州共有88个地点。 定量回归技术(QRT)与PCA集成,以估计洪水量。 共选择总共八个集水区作为预测变量。 应用休假验证以使用评估诊断的集合来确定开发统计模型的效率。 发现具有QRT模型的PCA不执行良好,而用较小的尺寸集群形成的集群/组更好地执行(中值相对误差值范围为22%至37%),而不是其他簇/组。 通过多元线性回归技术在集群/组中的异质性与洪水量预测的精度之间没有找到连接。

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