Application of machine learning-based surrogate models for urban flood depth modeling in Ho Chi Minh City, Vietnam-Reference-Cited by-同舟云学术

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Application of machine learning-based surrogate models for urban flood depth modeling in Ho Chi Minh City, Vietnam

Published:2024-01 Issue: Volume:150 Page:111031
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Dang Thanh Quang,Tran Ba Hoang,Le Quyen Ngoc,Dang Thanh Duc,Tanim Ahad Hasan,Pham Quoc Bao,Bui Van Hieu,Mai Son T.,Thanh Phong Nguyen,Anh Duong Tran

Funder

Department of Science and Technology, Ministry of Science and Technology, India

Publisher

Elsevier BV

Subject

Software

Reference96 articles.

1. Perspective on uncertainty quantification and reduction in compound flood modeling and forecasting;Abbaszadeh;Iscience,2022

2. Application of surrogate models in estimation of storm surge: a comparative assessment;Al Kajbaf;Appl. Soft Comput.,2020

3. Linear discriminant analysis-a brief tutorial;Balakrishnama;Inst. Signal Inf. Process.,1998

4. Surrogate modeling of joint flood risk across coastal watersheds;Bass;J. Hydrol.,2018

5. Random forest in remote sensing: a review of applications and future directions;Belgiu;ISPRS J. Photogramm. Remote Sens.,2016

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2. Enhancing stormwater network overflow prediction: investigation of ensemble learning models;Acta Geophysica;2024-07-10

3. Geographic heterogeneity of activation functions in urban real-time flood forecasting: Based on seasonal trend decomposition using Loess-Temporal Convolutional Network-Gated Recurrent Unit model;Journal of Hydrology;2024-06

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