气候变化领域集成服务门户(CCPortal): Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm

CCPortal

DOI	10.1007/s11069-021-04646-4
	Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm
	Xiong B.; Li R.; Ren D.; Liu H.; Xu T.; Huang Y.
发表日期	2021
ISSN	0921030X
起始页码	1559
结束页码	1575
卷号	107 期号:2
英文摘要	Flooding is a natural disaster that threatens people’s lives and causes economic losses. The accurate prediction of water level is of great significance for flood prevention. This study aimed to predict water levels in Wuhan City, which is located in the downstream of the Three Gorges Reservoir Region. In order to improve the accuracy of flood prediction, the AdaBoost algorithm was used to optimize a traditional back propagation neural network (BPNN) in order to resolve the slow convergence speed and local minimum in water level prediction. The improved BPNN was then employed to predict the water level in the study area for prediction intervals of 1 h, 3 h, and 5 h, respectively. Compared with the original BPNN, a generalized regression neural network, and a combination of a genetic algorithm and the original BPNN, the improved BPNN achieved superior water-level prediction. Additionally, the performance of the constructed model was evaluated using the mean absolute error, root-mean-square error (RMSE), mean absolute percentage error (MAPE), the correlation coefficients between the predicted and actual values of water level, and the frequency histograms of the prediction error. The results indicate that the improved BPNN model had a lower prediction error and show a reasonable normal distribution. Therefore, it is concluded that this model is suitable for the prediction of water level. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
关键词	AdaBoost Back propagation neural network Flood Water level
英文关键词	accuracy assessment; algorithm; artificial neural network; back propagation; flooding; prediction; reservoir; water level; China; Hubei; Three Gorges Reservoir; Wuhan
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206677
作者单位	College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang, Hubei 443002, China; Hubei Engineering Technology Research Center for Farmland Environment Monitoring, China Three Gorges University, Yichang, Hubei 443002, China; Engineering Research Center of Eco-Environment in the Three Gorges Reservoir Region of Ministry of Education, China Three Gorges University, Yichang, Hubei 443002, China
推荐引用方式 GB/T 7714	Xiong B.,Li R.,Ren D.,et al. Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm[J],2021,107(2).
APA	Xiong B.,Li R.,Ren D.,Liu H.,Xu T.,&Huang Y..(2021).Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm.Natural Hazards,107(2).
MLA	Xiong B.,et al."Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm".Natural Hazards 107.2(2021).