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Dam deformation analysis based on BPNN merging models 被引量:1
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作者 Jingui Zou Kien-Trinh Thi Bui +1 位作者 Yangxuan Xiao Chinh Van Doan 《Geo-Spatial Information Science》 SCIE CSCD 2018年第2期149-157,共9页
Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the people.In this paper,dam horizont... Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the people.In this paper,dam horizontal displacement is analyzed and then forecasted using three methods:the multi-regression model,the seasonal integrated auto-regressive moving average(SARIMA)model and the back-propagation neural network(BPNN)merging models.The monitoring data of the Hoa Binh Dam in Vietnam,including horizontal displacement,time,reservoir water level,and air temperature,are used for the experiments.The results indicate that all of these three methods can approximately describe the trend of dam deformation despite their different forecast accuracies.Hence,their short-term forecasts can provide valuable references for the dam safety. 展开更多
关键词 dam deformation analysis multi-regression model Back-propagation Neural Network(BPNN) Seasonal Integrated Auto-regressive Moving Average(SARIMA)model merging model
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