干旱区生态环境知识资源中心(Arid): Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation

Arid

DOI	10.1016/j.jhydrol.2019.03.004
	Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation
	Al-Sudani, Zainab Abdulelah 1; Salih, Sinan Q.2; Sharafati, Ahmad 3; Yaseen, Zaher Mundher 4
通讯作者	Yaseen, Zaher Mundher
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2019
卷号	573 页码:1-12
英文摘要	Among several components of the hydrology cycle, streamflow is one of the essential process necessarily needed to be studied. The establishment of an accurate and reliable forecasting soft computing model for this process is highly vital for water resource planning and management. The influence of the climatological environment on streamflow is central and studying its influence is very significant from the hydrology perspective. It has been noticed that the application of machine learning models considerably become predominant in solving and capturing the complexity of hydrological applications. This research presents the implementation of a novel hybrid model called Multivariate Adaptive Regression Spline integrated with Differential Evolution (MARS-DE) to forecast streamflow pattern in semi-arid region. To achieve this, monthly time series streamflow data at Baghdad station, coordinated at Tigris River, Iraq, is inspected. For the model validation, Least Square Support Vector Regression (LSSVR) and standalone MARS models are conducted. To demonstrate the analysis of the undertaken models, several statistical indicators are computed to verify the modeling accuracies. Based on the achieved results, the MARS-DE model exhibited an excellent hybrid predictive modeling capability for monthly time scale streamflow in semi-arid region. Quantitatively; MARS-DE, LSSVR and MARS models achieved the minimum root mean square error (RMSE) and mean absolute error (MAE) values of 46.64-35.25 m(3)/s, 57.50-49.20 m(3)/s and 78.01-62.65 m(3)/s, respectively. In conclusion, several perspectives are suggested for further studies to enhance the forecasting capability of the model.
英文关键词	MARS-DE Streamflow simulation Semi-arid environment Antecedent values
类型	Article
语种	英语
国家	Iraq ; Iran ; Vietnam
收录类别	SCI-E
WOS记录号	WOS:000474327800001
WOS关键词	SUPPORT VECTOR MACHINE ; ARTIFICIAL-INTELLIGENCE ; RIVER-BASIN ; SHORT-TERM ; NETWORK ; OPTIMIZATION ; PREDICTION ; WAVELET ; MARS ; ALGORITHMS
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217146
作者单位	1.Univ Baghdad, Water Resources Dept, Coll Engn, Baghdad, Iraq; 2.Univ Anbar, Comp Sci Dept, Coll Comp Sci & Informat Technol, Ramadi, Iraq; 3.Islamic Azad Univ, Dept Civil Engn, Sci & Res Branch, Tehran, Iran; 4.Ton Duc Thang Univ, Fac Civil Engn, Sustainable Dev Civil Engn Res Grp, Ho Chi Minh City, Vietnam
推荐引用方式 GB/T 7714	Al-Sudani, Zainab Abdulelah,Salih, Sinan Q.,Sharafati, Ahmad,et al. Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation[J],2019,573:1-12.
APA	Al-Sudani, Zainab Abdulelah,Salih, Sinan Q.,Sharafati, Ahmad,&Yaseen, Zaher Mundher.(2019).Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation.JOURNAL OF HYDROLOGY,573,1-12.
MLA	Al-Sudani, Zainab Abdulelah,et al."Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation".JOURNAL OF HYDROLOGY 573(2019):1-12.