Knowledge Resource Center for Ecological Environment in Arid Area
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, Huanhuan1; Lu, Yudong1; Zheng, Ce1; Yang, Mi2; Li, Shuangli3 | |
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). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。