A prediction model for local scour depth based on BP and GA-BP neural network. Issue 1 (June 2020)

• Record Type: Journal Article
• Authors: Dong, Haiyang; Chong, Lin; Zhou, Hanyu; Li, Zongyu
• Is Part Of: IOP conference series. Volume 525:Issue 1(2020)
• Publication Date: 2020-06
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/525/1/012005
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: A prediction model for the local scouring depth at bridge piers is built using BP and GA-BP neural network method. Measured data is collected from laboratory tests and field observation to work as train set of the predicting model which is verified by the measured data of Hangzhou Bay Bridge. The result shows that the predicted values of the local scour depth of the piers obtained by the two models are in good agreement with the measured values, which is more suitable than the existing general formula. What's more, GA-BP model performs better than BP model.