水利学报2017，Vol.48Issue(4)：390-397,407,9.DOI:10.13243/j.cnki.slxb.20150978
基于k-最近邻筛选的BMA集合预报模型研究
Study on the bayesian model averaging coupling with the k-nearest neighbor selection
摘要
Abstract
The BMA (Bayesian model averaging) is a multi-model ensemble forecasting algorithm based on the Bayesian formula to estimate the posterior probability distribution of forecasting variables.The performance of BMA depends largely on the quality of its training datasets.However,there are a lot of redundant samples,which are inconsistent with the current flow state and affect the accuracy and the reliability of BMA forecasts.In this study,the k-nearest neighbor (KNN) method is applied to address the similarities between the historical samples and the most recent flood process to reduce the influence of redundant samples on the parameter estimation of BMA.Two cases of BMA,i.e.with the use of KNN sample selection (namely KBMA) and the original one,are investigated and compared at the Wangjiaba catchment located in the upper region of the Huai River basin.The ensemble means of these two cases were examined against the observations and the forecasts from their ensemble members to test the efficiency of their deterministic forecasts.Additionally,the probabilistic forecasts from these two cases were intercompared on the basis of two assessment criteria including Coverage Rate and Ranked Probability Score.The results indicate that the KBMA can produce improved deterministic and probabilistic forecasts as compared to the original BMA.By employing the KNN sample selection method,the KBMA is able to adjust its parameters according to the real time state of the flood processes and ensemble members,rather than adjusting them through the use of all samples.Our analysis demonstrates that the KNN sample selection method has the potential to substantially improve BMA ensemble forecasts.关键词
集合预报/样本筛选/k-最近邻/贝叶斯模型平均法/高斯混合模型Key words
ensemble forecast/sample selection method/k-nearest neighbor/Bayesian Model Averaging/Gaussian mixture model分类
天文与地球科学引用本文复制引用
刘开磊,李致家,姚成,韩通,钟栗,孙如飞..基于k-最近邻筛选的BMA集合预报模型研究[J].水利学报,2017,48(4):390-397,407,9.基金项目
国家重点研发计划项目(2016YFC0400909) （2016YFC0400909）
国家自然科学基金项目(41130639,51179045,41101017,41201028) （41130639,51179045,41101017,41201028）
