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DOI | 10.1002/hyp.13391 |
Wavelet-copula-based mutual information for rainfall forecasting applications | |
Abdourahamane, Zakari Seybou1,2; Acar, Resat2; Serkan, Senocak2 | |
发表日期 | 2019 |
ISSN | 0885-6087 |
EISSN | 1099-1085 |
卷号 | 33期号:7页码:1127-1142 |
英文摘要 | Under a climate change, the physical factors that influence the rainfall regime are diverse and difficult to predict. The selection of skilful inputs for rainfall forecasting models is, therefore, more challenging. This paper combines wavelet transform and Frank copula function in a mutual information-based input variable selection (IVS) for non-linear rainfall forecasting models. The marginal probability density functions (PDFs) of a set of potential rainfall predictors and the rainfall series (predictand) were computed using a wavelet density estimator. The Frank copula function was applied to compute the joint PDF of the predictors and the predictand from their marginal PDFs. The relationship between the rainfall series and the potential predictors was assessed based on the mutual information computed from their marginal and joint PDFs. Finally, the minimum redundancy maximum relevance was used as an IVS stopping criterion to determine the number of skilful input variables. The proposed approach was applied to four stations of the Nigerien Sahel with rainfall series spanning the period 1950-2016 by considering 24 climate indices as potential predictors. Adaptive neuro-fuzzy inference system, artificial neural networks, and random forest-based forecast models were used to assess the skill of the proposed IVS method. The three forecasting models yielded satisfactory results, exhibiting a coefficient of determination between 0.52 and 0.69 and a mean absolute percentage error varying from 13.6% to 21%. The adaptive neuro-fuzzy inference system performed better than the other models at all the stations. A comparison made with KDE-based mutual information showed the advantage of the proposed wavelet-copula approach. |
WOS研究方向 | Water Resources |
来源期刊 | HYDROLOGICAL PROCESSES |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/95258 |
作者单位 | 1.Ataturk Univ, Grad Sch Nat & Appl Sci, Erzurum, Turkey; 2.Ataturk Univ, Dept Civil Engn, TR-25030 Erzurum, Turkey |
推荐引用方式 GB/T 7714 | Abdourahamane, Zakari Seybou,Acar, Resat,Serkan, Senocak. Wavelet-copula-based mutual information for rainfall forecasting applications[J],2019,33(7):1127-1142. |
APA | Abdourahamane, Zakari Seybou,Acar, Resat,&Serkan, Senocak.(2019).Wavelet-copula-based mutual information for rainfall forecasting applications.HYDROLOGICAL PROCESSES,33(7),1127-1142. |
MLA | Abdourahamane, Zakari Seybou,et al."Wavelet-copula-based mutual information for rainfall forecasting applications".HYDROLOGICAL PROCESSES 33.7(2019):1127-1142. |
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