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DOI	10.1016/j.pce.2023.103451
	An improved adaptive neuro-fuzzy inference system for hydrological drought prediction in Algeria
	Achite, Mohammed; Gul, Enes; Elshaboury, Nehal; Jehanzaib, Muhammad; Mohammadi, Babak; Mehr, Ali Danandeh
通讯作者	Mohammadi, B
来源期刊	PHYSICS AND CHEMISTRY OF THE EARTH
ISSN	1474-7065
EISSN	1873-5193
出版年	2023
卷号	131
英文摘要	Drought has negative impacts on water resources, food security, soil degradation, desertification and agricultural productivity. The meteorological and hydrological droughts prediction using standardized precipitation/runoff indices (SPI/SRI) is crucial for effective water resource management. In this study, we suggest ANFISWCA, an adaptive neuro-fuzzy inference system (ANFIS) optimized by the water cycle algorithm (WCA), for hydrological drought forecasting in semi-arid regions of Algeria. The new model was used to predict SRI at 3-, 6-, 9-, and 12 -month accumulation periods in the Wadi Mina basin, Algeria. The results of the model were assessed using four criteria; determination coefficient, mean absolute error, variance accounted for, and root mean square error, and compared with those of the standalone ANFIS model. The findings suggested that throughout the testing phase at all the sub-basins, the proposed hybrid model outperformed the conventional model for estimating drought. This study indicated that the WCA algorithm enhanced the ANFIS model's drought forecasting accuracy. The pro-posed model could be employed for forecasting drought at multi-timescales, deciding on remedial strategies for dealing with drought at study stations, and aiding in sustainable water resources management.
英文关键词	Hydrological drought Hybrid model ANFIS Water cycle algorithm semi -arid regions
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:001052900300001
WOS关键词	ALGORITHM ; WAVELET ; INDEX ; BOOTSTRAP ; FRAMEWORK ; MODELS ; FLOODS ; ANFIS ; SCALE ; SPI
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398003
推荐引用方式 GB/T 7714	Achite, Mohammed,Gul, Enes,Elshaboury, Nehal,et al. An improved adaptive neuro-fuzzy inference system for hydrological drought prediction in Algeria[J],2023,131.
APA	Achite, Mohammed,Gul, Enes,Elshaboury, Nehal,Jehanzaib, Muhammad,Mohammadi, Babak,&Mehr, Ali Danandeh.(2023).An improved adaptive neuro-fuzzy inference system for hydrological drought prediction in Algeria.PHYSICS AND CHEMISTRY OF THE EARTH,131.
MLA	Achite, Mohammed,et al."An improved adaptive neuro-fuzzy inference system for hydrological drought prediction in Algeria".PHYSICS AND CHEMISTRY OF THE EARTH 131(2023).