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DOI	10.2166/wcc.2018.113
	Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates
	Araghi A.; Adamowski J.; Martinez C.J.
发表日期	2020
ISSN	20402244
起始页码	39
结束页码	53
卷号	11 期号:1
英文摘要	Reference evapotranspiration (ETo ) is one of the most important factors in the hydrologic cycle and water balance studies. In this study, the performance of three simple and three wavelet hybrid models were compared to estimate ETo in three different climates in Iran, based on different combinations of input variables. It was found that the wavelet-artificial neural network was the best model, and multiple linear regression (MLR) was the worst model in most cases, although the performance of the models was related to the climate and the input variables used for modeling. Overall, it was found that all models had good accuracy in terms of estimating daily ETo. Also, it was found in this study that large numbers of decomposition levels via the wavelet transform had noticeable negative effects on the performance of the wavelet-based models, especially for the wavelet-adaptive network-based fuzzy inference system and wavelet-MLR, but in contrast, the type of db wavelet function did not have a detectable effect on the performance of the wavelet-based models. © IWA Publishing 2020.
英文关键词	Artificial intelligence; Discrete wavelet transform; Multiple linear regression; Reference evapotranspiration
语种	英语
scopus关键词	Evapotranspiration; Fuzzy inference; Fuzzy neural networks; Linear regression; Wavelet decomposition; Adaptive network based fuzzy inference system; Decomposition level; Hydrologic cycles; Input variables; Multiple linear regressions; Reference evapotranspiration; Water balance; Wavelet based models; Climate models; climate conditions; comparative study; estimation method; evapotranspiration; hydrological cycle; performance assessment; water budget; wavelet analysis
来源期刊	Journal of Water and Climate Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/147946
作者单位	Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran; Department of Bioresource Engineering, Faculty of Agriculture and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, Canada; Department of Agricultural and Biological Engineering, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, United States
推荐引用方式 GB/T 7714	Araghi A.,Adamowski J.,Martinez C.J.. Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates[J],2020,11(1).
APA	Araghi A.,Adamowski J.,&Martinez C.J..(2020).Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates.Journal of Water and Climate Change,11(1).
MLA	Araghi A.,et al."Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates".Journal of Water and Climate Change 11.1(2020).