干旱区生态环境知识资源中心(Arid): Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia

Arid

DOI	10.1080/10106049.2021.1878291
	Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia
	Mallick, Javed; Talukdar, Swapan; Alsubih, Majed; Ahmed, Mohd.; Islam, Abu Reza Md Towfiqul; Shahfahad; Thanh, Nguyen Viet
通讯作者	Mallick, J (corresponding author), King Khalid Univ, Coll Engn, Dept Civil Engn, Abha, Saudi Arabia.
来源期刊	GEOCARTO INTERNATIONAL
ISSN	1010-6049
EISSN	1752-0762
出版年	2021-01
英文摘要	Groundwater scarcity is one of the most concerning issues in arid and semi-arid regions. In this study, we develop and validate a novel artificial intelligence that is a coupling of five ensemble benchmark algorithms e.g., artificial neural network (ANN), reduced-error pruning trees (REPTree), radial basis function (RBF), M5P and random forest (RF) with particle swarm optimization (PSO) for delineating GWP zones. Further, nine parameters used for the GWP modelling and to test and train the proposed PSO-based models. Additionally, this study proposes a receiver operating characteristic (ROC) based sensitivity analysis for GWP modelling. Multicollinearity test, information gain ratio, and correlation attribute evaluation methods used to choose important parameters for the proposed GWP model. The result shows that drainage density, elevation, and land use/land cover have a higher influence on the GWP using correlation attribute evaluation methods. Results showed that the hybrid PSO-RF model performed better than other proposed hybrid models.
英文关键词	ROC-based sensitivity particle swarm optimization Artificial intelligence groundwater Asir region
类型	Article ; Early Access
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000624993100001
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/352202
作者单位	[Mallick, Javed; Alsubih, Majed; Ahmed, Mohd.] King Khalid Univ, Coll Engn, Dept Civil Engn, Abha, Saudi Arabia; [Talukdar, Swapan] Univ Gour Banga, Dept Geog, Malda, India; [Islam, Abu Reza Md Towfiqul] Begum Rokeya Univ, Dept Disaster Management, Rangpur, Bangladesh; [Shahfahad] Jamia Millia Islamia, Urban Environm Remote Sensing Div, Fac Nat Sci, New Delhi, India; [Thanh, Nguyen Viet] Univ Transport & Commun, Fac Civil Engn, Hanoi, Vietnam
推荐引用方式 GB/T 7714	Mallick, Javed,Talukdar, Swapan,Alsubih, Majed,et al. Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia[J],2021.
APA	Mallick, Javed.,Talukdar, Swapan.,Alsubih, Majed.,Ahmed, Mohd..,Islam, Abu Reza Md Towfiqul.,...&Thanh, Nguyen Viet.(2021).Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia.GEOCARTO INTERNATIONAL.
MLA	Mallick, Javed,et al."Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia".GEOCARTO INTERNATIONAL (2021).