DOI: 10.1007/s11069-021-04597-w
论文题名: Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network
作者: Yao Y. ; Yang X. ; Lai S.H. ; Chin R.J.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 107, 期: 1 起始页码: 601
结束页码: 616
语种: 英语
中文关键词: Artificial neural network
; Coral reef
; solitary wave
; Tsunami hazard
; Wave run-up
英文关键词: artificial neural network
; Boussinesq equation
; coastal zone
; coral reef
; early warning system
; fringing reef
; hydrodynamic force
; machine learning
; nearshore dynamics
; prediction
; risk assessment
; solitary wave
; tsunami
; wave height
; wave runup
英文摘要: Modeling of tsunami wave interaction with coral reefs to date focuses mainly on the process-based numerical models. In this study, an alternative machine learning technique based on the multi-layer perceptron neural network (MLP-NN) is introduced to predict the tsunami-like solitary wave run-up over fringing reefs. Two hydrodynamic forcings (incident wave height, reef-flat water level) and four reef morphologic features (reef width, fore-reef slope, beach slope, reef roughness) are selected as the input variables and wave run-up on the back-reef beach is assigned as the output variable. A validated numerical model based on the Boussinesq equations is applied to provide a dataset consisting of 4096 runs for MLP-NN training and testing. Results analyses show that the MLP-NN consisting of one hidden layer with ten hidden neurons provides the best predictions for the wave run-up. Subsequently, model performances in view of individual input variables are accessed via an analysis of the percentage errors of the predictions. Finally, a mean impact value analysis is also conducted to evaluate the relative importance of the input variables to the output variable. In general, the adopted MLP-NN has high predictive capability for wave run-up over the reef-lined coasts, and it is an alternative but more efficient tool for potential use in tsunami early warning system or risk assessment projects. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169488
Appears in Collections: 气候变化与战略
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作者单位: School of Hydraulic Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China; Department of Civil Engineering, Faculty of Engineering, University of Malaya, Lembah Pantai, Kuala Lumpur, 50603, Malaysia; Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, Selangor 43000, Malaysia; Key Laboratory of Water-Sediment Sciences and Water Disaster Prevention of Hunan Province, Changsha, Hunan 410114, China
Recommended Citation:
Yao Y.,Yang X.,Lai S.H.,et al. Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network[J]. Natural Hazards,2021-01-01,107(1)