干旱区生态环境知识资源中心(Arid): Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria

Arid

DOI	10.3390/w15040765
	Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria
	Achite, Mohammed; Elshaboury, Nehal; Jehanzaib, Muhammad; Vishwakarma, Dinesh Kumar; Pham, Quoc Bao; Anh, Duong Tran; Abdelkader, Eslam Mohammed; Elbeltagi, Ahmed
通讯作者	Pham, QB
来源期刊	WATER
EISSN	2073-4441
出版年	2023
卷号	15 期号:4
英文摘要	Water resources, land and soil degradation, desertification, agricultural productivity, and food security are all adversely influenced by drought. The prediction of meteorological droughts using the standardized precipitation index (SPI) is crucial for water resource management. The modeling results for SPI at 3, 6, 9, and 12 months are based on five types of machine learning: support vector machine (SVM), additive regression, bagging, random subspace, and random forest. After training, testing, and cross-validation at five folds on sub-basin 1, the results concluded that SVM is the most effective model for predicting SPI for different months (3, 6, 9, and 12). Then, SVM, as the best model, was applied on sub-basin 2 for predicting SPI at different timescales and it achieved satisfactory outcomes. Its performance was validated on sub-basin 2 and satisfactory results were achieved. The suggested model performed better than the other models for estimating drought at sub-basins during the testing phase. The suggested model could be used to predict meteorological drought on several timescales, choose remedial measures for research basin, and assist in the management of sustainable water resources.
英文关键词	meteorological drought semi-arid regions support vector machine additive regression bagging random subspace random forest
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000942384600001
WOS关键词	RIVER-BASIN ; ENSEMBLE
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398988
推荐引用方式 GB/T 7714	Achite, Mohammed,Elshaboury, Nehal,Jehanzaib, Muhammad,et al. Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria[J],2023,15(4).
APA	Achite, Mohammed.,Elshaboury, Nehal.,Jehanzaib, Muhammad.,Vishwakarma, Dinesh Kumar.,Pham, Quoc Bao.,...&Elbeltagi, Ahmed.(2023).Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria.WATER,15(4).
MLA	Achite, Mohammed,et al."Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria".WATER 15.4(2023).