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Journal Articles

An Application of Machine Learning Algorithms on the Prediction of the Damage Level of Rubble-Mound Breakwaters

Susmita Saha, Soumen De, Satyasaran Changdar

Publisher: ASME

J. Offshore Mech. Arct. Eng. February 2024, 146(1): 011202.

Paper No: OMAE-22-1185

https://doi.org/10.1115/1.4062475

Published Online: May 24, 2023

View Article titled, An Application of Machine Learning Algorithms on the Prediction of the Damage Level of Rubble-Mound Breakwaters

Topics: Algorithms, Artificial neural networks, Breakwaters, Damage, Machine learning, Stability, Support vector machines

Journal Articles

Support Vector Machines Model of the Nonlinear Hydrodynamics of Fixed Cylinders

Yu Ma, Paul D. Sclavounos

Publisher: ASME

J. Offshore Mech. Arct. Eng. October 2021, 143(5): 051701.

Paper No: OMAE-20-1106

https://doi.org/10.1115/1.4049731

Published Online: February 12, 2021

View Article titled, Support Vector Machines Model of the Nonlinear Hydrodynamics of Fixed Cylinders

Topics: Stress, Support vector machines, Waves, Algorithms, Regression models, Cylinders, Seas, Nonlinear waves

Journal Articles

Real-Time Parameter Estimation of a Nonlinear Vessel Steering Model Using a Support Vector Machine

Haitong Xu, M. A. Hinostroza, Vahid Hassani, C. Guedes Soares

Publisher: ASME

J. Offshore Mech. Arct. Eng. December 2019, 141(6): 061606.

Paper No: OMAE-18-1212

https://doi.org/10.1115/1.4043806

Published Online: June 19, 2019

View Article titled, Real-Time Parameter Estimation of a Nonlinear Vessel Steering Model Using a Support Vector Machine

Topics: Parameter estimation, Ships, Support vector machines, Vessels

Journal Articles

Comparison of Various Surrogate Models to Predict Stress Intensity Factor of a Crack Propagating in Offshore Piping

Arvind Keprate, R. M. Chandima Ratnayake, Shankar Sankararaman

Publisher: ASME

J. Offshore Mech. Arct. Eng. December 2017, 139(6): 061401.

Paper No: OMAE-17-1055

https://doi.org/10.1115/1.4037290

Published Online: August 16, 2017

View Article titled, Comparison of Various Surrogate Models to Predict Stress Intensity Factor of a Crack Propagating in Offshore Piping

Topics: Finite element methods, Finite element model, Fracture (Materials), Stress, Polynomials, Underwater pipelines, Testing, Pipes, Artificial neural networks, Support vector machines

Journal Articles

Parameter Identification of Ship Maneuvering Model Based on Support Vector Machines and Particle Swarm Optimization

Weilin Luo, C. Guedes Soares, Zaojian Zou

Publisher: ASME

J. Offshore Mech. Arct. Eng. June 2016, 138(3): 031101.

Paper No: OMAE-13-1028

https://doi.org/10.1115/1.4032892

Published Online: April 6, 2016

View Article titled, Parameter Identification of Ship Maneuvering Model Based on Support Vector Machines and Particle Swarm Optimization

Topics: Particle swarm optimization, Ships, Support vector machines

Journal citation

NARROW

An Application of Machine Learning Algorithms on the Prediction of the Damage Level of Rubble-Mound Breakwaters

Support Vector Machines Model of the Nonlinear Hydrodynamics of Fixed Cylinders

Real-Time Parameter Estimation of a Nonlinear Vessel Steering Model Using a Support Vector Machine

Comparison of Various Surrogate Models to Predict Stress Intensity Factor of a Crack Propagating in Offshore Piping

Parameter Identification of Ship Maneuvering Model Based on Support Vector Machines and Particle Swarm Optimization

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

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An Application of Machine Learning Algorithms on the Prediction of the Damage Level of Rubble-Mound Breakwaters

Support Vector Machines Model of the Nonlinear Hydrodynamics of Fixed Cylinders

Real-Time Parameter Estimation of a Nonlinear Vessel Steering Model Using a Support Vector Machine

Comparison of Various Surrogate Models to Predict Stress Intensity Factor of a Crack Propagating in Offshore Piping

Parameter Identification of Ship Maneuvering Model Based on Support Vector Machines and Particle Swarm Optimization

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

Opportunities

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