气候变化领域集成服务门户(CCPortal): Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network

CCPortal

DOI	10.1007/s11069-021-04597-w
	Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network
	Yao Y.; Yang X.; Lai S.H.; Chin R.J.
发表日期	2021
ISSN	0921030X
起始页码	601
结束页码	616
卷号	107 期号:1
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.
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
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/206689
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
推荐引用方式 GB/T 7714	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],2021,107(1).
APA	Yao Y.,Yang X.,Lai S.H.,&Chin R.J..(2021).Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network.Natural Hazards,107(1).
MLA	Yao Y.,et al."Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network".Natural Hazards 107.1(2021).