Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network

Yao, Yu and Yang, Xiaoxiao and Lai, Sai Hin and Chin, Ren Jie (2021) Predicting tsunami-like solitary wave run-up over fringing reefs using the multi-layer perceptron neural network. Natural Hazards, 107 (1). pp. 601-616. ISSN 0921-030X, DOI https://doi.org/10.1007/s11069-021-04597-w.

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Abstract

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.

Item Type: Article
Funders: National Natural Science Foundation of China (NSFC) (51979013), National Natural Science Foundation of China (NSFC) (51679014), Hunan Provincial Education Department (18A116)
Uncontrolled Keywords: Wave run-up; Artificial neural network; Tsunami hazard; solitary wave; Coral reef
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering > Department of Civil Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 28 Mar 2022 01:56
Last Modified: 28 Mar 2022 01:56
URI: http://eprints.um.edu.my/id/eprint/26590

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