• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Geosciences >An Attempt to Use Non-Linear Regression Modelling Technique in Long-Term Seasonal Rainfall Forecasting for Australian Capital Territory
【24h】

An Attempt to Use Non-Linear Regression Modelling Technique in Long-Term Seasonal Rainfall Forecasting for Australian Capital Territory

机译：在澳大利亚首都领地的长期季节性降雨预报中使用非线性回归建模技术的尝试

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The objective of this research is the assessment of the efficiency of a non-linear regression technique in predicting long-term seasonal rainfall. The non-linear models were developed using the lagged (past) values of the climate drivers, which have a significant correlation with rainfall. More specifically, the capabilities of SEIO (South-eastern Indian Ocean) and ENSO (El Nino Southern Oscillation) were assessed in reproducing the rainfall characteristics using the non-linear regression approach. The non-linear models developed were tested using the individual data sets, which were not used during the calibration of the models. The models were assessed using the commonly used statistical parameters, such as Pearson correlations (R), root mean square error (RMSE), mean absolute error (MAE) and index of agreement (d). Three rainfall stations located in the Australian Capital Territory (ACT) were selected as a case study. The analysis suggests that the predictors which has the highest correlation with the predictands do not necessarily produce the least errors in rainfall forecasting. The non-linear regression was able to predict seasonal rainfall with correlation coefficients varying from 0.71 to 0.91. The outcomes of the analysis will help the watershed management authorities to adopt efficient modelling technique by predicting long-term seasonal rainfall.
机译：这项研究的目的是评估非线性回归技术在预测长期季节性降雨中的效率。非线性模型是使用气候驱动因素的滞后（过去）值开发的，该值与降雨有显着相关性。更具体地说，使用非线性回归方法评估了SEIO（印度洋东南部）和ENSO（厄尔尼诺南部涛动）的能力，以再现降雨特征。使用单独的数据集测试开发的非线性模型，该数据集在模型校准期间未使用。使用常用的统计参数，例如皮尔逊相关性（R），均方根误差（RMSE），平均绝对误差（MAE）和一致性指数（d），对模型进行评估。案例研究选择了位于澳大利亚首都特区（ACT）的三个降雨站。分析表明，与预报相关性最高的预报器不一定在降雨预报中产生最少的误差。非线性回归能够预测季节降雨，相关系数在0.71至0.91之间变化。分析结果将有助于流域管理当局通过预测长期季节性降雨来采用有效的建模技术。

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