DOI: 10.5194/hess-18-2711-2014
Scopus记录号: 2-s2.0-84905233687
论文题名: Comment on "A hybrid model of self organizing maps and least square support vector machine for river flow forecasting" by Ismail et al. (2012)
作者: Fahimi F ; , El-Shafie A ; H
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 7 起始页码: 2711
结束页码: 2714
语种: 英语
Scopus关键词: Conformal mapping
; Forecasting
; Stream flow
; Water management
; Auto-regressive integrated moving average
; Earth system science
; Forecasting techniques
; Least square support vector machines
; Least squares support vector machines
; River flow forecasting
; River flow prediction
; Waterresource management
; Self organizing maps
英文摘要: Without a doubt, river flow forecasting is one of the most important issues in water engineering field. There are lots of forecasting techniques that have successfully been utilized by previously conducted studies in water resource management and water engineering. The study of Ismail et al. (2012), which was published in the journal Hydrology and Earth System Sciences in 2012, was a valuable piece of research that investigated the combination of two effective methods (self-organizing map and least squares support vector machine) for river flow forecasting. The goal was to make a comparison between the performances of self organizing map and least square support vector machine (SOM-LSSVM), autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and least squares support vector machine (LSSVM) models for river flow prediction. This comment attempts to focus on some parts of the original paper that need more discussion. The emphasis here is to provide more information about the accuracy of the observed river flow data and the optimum map size for SOM mode as well. © Author(s) 2014. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78185
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Civil and Structural Engineering, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia
Recommended Citation:
Fahimi F,, El-Shafie A,H. Comment on "A hybrid model of self organizing maps and least square support vector machine for river flow forecasting" by Ismail et al. (2012)[J]. Hydrology and Earth System Sciences,2014-01-01,18(7)