干旱区生态环境知识资源中心(Arid): Groundwater Level Prediction for the Arid Oasis of Northwest China Based on the Artificial Bee Colony Algorithm and a Back-propagation Neural Network with Double Hidden Layers

Arid

DOI	10.3390/w11040860
	Groundwater Level Prediction for the Arid Oasis of Northwest China Based on the Artificial Bee Colony Algorithm and a Back-propagation Neural Network with Double Hidden Layers
	Li, Huanhuan 1; Lu, Yudong 1; Zheng, Ce 1; Yang, Mi 2; Li, Shuangli 3
通讯作者	Lu, Yudong
来源期刊	WATER
EISSN	2073-4441
出版年	2019
卷号	11 期号:4
英文摘要	Groundwater is crucial for economic and agricultural development, particularly in arid areas where surface water resources are extremely scarce. The prediction of groundwater levels is essential for understanding groundwater dynamics and providing scientific guidance for the rational utilization of groundwater resources. A back propagation (BP) neural network based on the artificial bee colony (ABC) optimization algorithm was established in this study to accurately predict groundwater levels in the overexploited arid areas of Northwest China. Recharge, exploitation, rainfall, and evaporation were used as input factors, whereas groundwater level was used as the output factor. Results showed that the fitting accuracy, convergence rate, and stabilization of the ABC-BP model are better than those of the particle swarm optimization (PSO-BP), genetic algorithm (GA-BP), and BP models, thereby proving that the ABC-BP model can be a new method for predicting groundwater levels. The ABC-BP model with double hidden layers and a topology structure of 4-7-3-1, which overcame the overfitting problem, was developed to predict groundwater levels in Yaoba Oasis from 2019 to 2030. The prediction results of different mining regimes showed that the groundwater level in the study area will gradually decrease as exploitation quantity increases and then undergo a decline stage given the existing mining condition of 40 million m(3)/year. According to the simulation results under different scenarios, the most appropriate amount of groundwater exploitation should be maintained at 31 million m(3)/year to promote the sustainable development of groundwater resources in Yaoba Oasis.
英文关键词	artificial bee colony algorithm double hidden layers back-propagation neural network groundwater level prediction arid oasis
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	Green Submitted, gold
收录类别	SCI-E
WOS记录号	WOS:000473105700230
WOS关键词	GENETIC ALGORITHM ; MODEL ; DECOLORIZATION ; OPTIMIZATION ; RESOURCES ; SYSTEMS ; DESIGN
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/2XILL650/219191
作者单位	1.Changan Univ, Sch Environm Sci & Engn, Minist Educ, Key Lab Subsurface Hydrol & Ecol Effects Arid Reg, Xian 710054, Shaanxi, Peoples R China; 2.Shaanxi Yining Construct Engn Co Ltd, Xian 710065, Shaanxi, Peoples R China; 3.Yanbian Univ, Sch Sci, Yanji 133200, Peoples R China
推荐引用方式 GB/T 7714	Li, Huanhuan,Lu, Yudong,Zheng, Ce,et al. Groundwater Level Prediction for the Arid Oasis of Northwest China Based on the Artificial Bee Colony Algorithm and a Back-propagation Neural Network with Double Hidden Layers[J],2019,11(4).
APA	Li, Huanhuan,Lu, Yudong,Zheng, Ce,Yang, Mi,&Li, Shuangli.(2019).Groundwater Level Prediction for the Arid Oasis of Northwest China Based on the Artificial Bee Colony Algorithm and a Back-propagation Neural Network with Double Hidden Layers.WATER,11(4).
MLA	Li, Huanhuan,et al."Groundwater Level Prediction for the Arid Oasis of Northwest China Based on the Artificial Bee Colony Algorithm and a Back-propagation Neural Network with Double Hidden Layers".WATER 11.4(2019).