A Study of Machine Learning Model for Prediction of Swelling Waves Occurrence on East Sea

Kang, Donghoon; Oh, Sejong

doi:10.14801/jkiit.2019.17.9.11

KIIT

2019

DOI: 10.14801/jkiit.2019.17.9.11

|View full text |Cite

A Study of Machine Learning Model for Prediction of Swelling Waves Occurrence on East Sea

Donghoon Kang¹,

Sejong Oh²

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Review on Applications of Machine Learning in Coastal and Ocean Engineering

Kim

Lee

2022

J. Ocean Eng. Technol.

View full text Add to dashboard Cite

Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.

show abstract

Review on Applications of Machine Learning in Coastal and Ocean Engineering

Kim

Lee

2022

J. Ocean Eng. Technol.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A Study of Machine Learning Model for Prediction of Swelling Waves Occurrence on East Sea

Cited by 1 publication

References 7 publications

Review on Applications of Machine Learning in Coastal and Ocean Engineering

Review on Applications of Machine Learning in Coastal and Ocean Engineering

Contact Info

Product

Resources

About