globalchange  > 气候变化与战略
DOI: 10.1007/s11069-021-04646-4
论文题名:
Prediction of flooding in the downstream of the Three Gorges Reservoir based on a back propagation neural network optimized using the AdaBoost algorithm
作者: Xiong B.; Li R.; Ren D.; Liu H.; Xu T.; Huang Y.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 107, 期:2
起始页码: 1559
结束页码: 1575
语种: 英语
中文关键词: 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
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.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169476
Appears in Collections:气候变化与战略

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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

Recommended Citation:
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]. Natural Hazards,2021-01-01,107(2)
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