干旱区生态环境知识资源中心(Arid): Spatial mapping of water spring potential using four data mining models

Arid

DOI	10.2166/ws.2023.087
	Spatial mapping of water spring potential using four data mining models
	Al-Shabeeb, Abdel Rahman; Hamdan, Ibraheem; Al-Fugara, A'kif; Al-Adamat, Rida; Alrawashdeh, Mohammed
通讯作者	Al-Shabeeb, AR
来源期刊	WATER SUPPLY
ISSN	1606-9749
EISSN	1607-0798
出版年	2023
卷号	23 期号:5 页码:1743-1759
英文摘要	Population growth and overexploitation of water resources pose ongoing pressure on groundwater resources. This study compares the capability of four data mining methods, namely, boosted regression tree (BRT), random forest (RF), multivariate adaptive regression spline (MARS), and support vector machine (SVM), for water spring potential mapping (WSPM) in Al Kark Governorate, East of the Dead Sea, Jordan. Overall, 200 spring locations and 13 predictor variables were considered for model building and validation. The four models were calibrated and trained on 70% of the spring locations (i.e., 140 locations) and their predictive accuracy was evaluated on the remaining 30% of the locations (i.e., 60 locations). The area under the receiver operating characteristic curve (AUROCC) was employed as the performance measure for the evaluation of the accuracy of the constructed models. Results of model accuracy assessment based on the AUROCC revealed that the performance of the RF model (AUROCC = 0.742) was better than that of any other model (AUROCC SVM = 0.726, AUROCC MARS= 0.712, and AUROCC BRT = 0.645).
英文关键词	data mining Karak semi-arid area springs potential
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:000967930300001
WOS关键词	SUPPORT VECTOR MACHINE ; RANDOM FOREST ; GROUNDWATER ; REGRESSION ; PREDICTION ; MANAGEMENT ; REGION ; SITES ; ZONES
WOS类目	Engineering, Environmental ; Environmental Sciences ; Water Resources
WOS研究方向	Engineering ; 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/2XILL650/399166
推荐引用方式 GB/T 7714	Al-Shabeeb, Abdel Rahman,Hamdan, Ibraheem,Al-Fugara, A'kif,et al. Spatial mapping of water spring potential using four data mining models[J],2023,23(5):1743-1759.
APA	Al-Shabeeb, Abdel Rahman,Hamdan, Ibraheem,Al-Fugara, A'kif,Al-Adamat, Rida,&Alrawashdeh, Mohammed.(2023).Spatial mapping of water spring potential using four data mining models.WATER SUPPLY,23(5),1743-1759.
MLA	Al-Shabeeb, Abdel Rahman,et al."Spatial mapping of water spring potential using four data mining models".WATER SUPPLY 23.5(2023):1743-1759.