干旱区生态环境知识资源中心(Arid): Estimation of land subsidence using coupled particle swarm optimization and genetic algorithm: the case of Damghan aquifer

Arid

DOI	10.2166/ws.2024.002
	Estimation of land subsidence using coupled particle swarm optimization and genetic algorithm: the case of Damghan aquifer
	Ashouri, Reza; Emamgholizadeh, Samad; Haji Kandy, Hooman; Mehdizadeh, S. Sadjad; Jamali, Saeed
通讯作者	Emamgholizadeh, S
来源期刊	WATER SUPPLY
ISSN	1606-9749
EISSN	1607-0798
出版年	2024
卷号	24 期号:2 页码:416-435
英文摘要	Land subsidence, which is mainly caused by the over-extraction of groundwater, is one of the most important problems in arid and semi-arid regions. In the present study, seven factors affecting the land subsidence, i.e., the types of subsoil, land use, pumping, recharge, the thickness of the plain aquifer, distance to the fault, and groundwater depletion, were considered as input data for the ALPRIFT framework and intelligence models to map both subsidence vulnerability index and prediction of land subsidence. The hybrid of particle swarm optimization (PSO) and genetic algorithm (GA) (hybrid PSO-GA) was then used to optimize the weights of the input layers and the estimation of the land subsidence. The capability of the PSO-GA at the prediction of land subsidence was compared with the typical GA model and gene expression programming (GEP). The statistical indices coefficient of correlation (R2), root mean square error (RMSE), and mean absolute error (MAE) were used to assess the accuracy and reliability of the applied models. The results showed that the hybrid PSO-GA model had R-2, RMSE, and MAE equal to 0.91, 1.11 cm, and 0.94 cm, respectively. In comparison with the GA and GEP models, the hybrid PSO-GA model improved the prediction of land subsidence and reduced RMSE by 24.30 and 16.80%, respectively.
英文关键词	alluvial aquifer artificial intelligence model land subsidence optimization
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:001141098600001
WOS关键词	DIFFERENTIAL SAR INTERFEROMETRY ; GROUNDWATER ; SYSTEM ; LEVEL
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/2XILL650/405937
推荐引用方式 GB/T 7714	Ashouri, Reza,Emamgholizadeh, Samad,Haji Kandy, Hooman,et al. Estimation of land subsidence using coupled particle swarm optimization and genetic algorithm: the case of Damghan aquifer[J],2024,24(2):416-435.
APA	Ashouri, Reza,Emamgholizadeh, Samad,Haji Kandy, Hooman,Mehdizadeh, S. Sadjad,&Jamali, Saeed.(2024).Estimation of land subsidence using coupled particle swarm optimization and genetic algorithm: the case of Damghan aquifer.WATER SUPPLY,24(2),416-435.
MLA	Ashouri, Reza,et al."Estimation of land subsidence using coupled particle swarm optimization and genetic algorithm: the case of Damghan aquifer".WATER SUPPLY 24.2(2024):416-435.