[HTML][HTML] Review of the application of Artificial Neural Networks in ocean engineering

NP Juan, VN Valdecantos - Ocean Engineering, 2022 - Elsevier
Abstract Artificial Neural Networks (ANNs) were firstly used to model ocean engineering
problems in the decade of 1990s. Since then, this soft-modelling technique has proved …

[HTML][HTML] Uncertainties in the application of artificial neural networks in ocean engineering

NP Juan, C Matutano, VN Valdecantos - Ocean Engineering, 2023 - Elsevier
Abstract Artificial Neural Networks (ANNs) are becoming more popular to model ocean
engineering problems. With the development of Artificial Intelligence, data-driven models …

[HTML][HTML] Living with floods using state-of-the-art and geospatial techniques: flood mitigation alternatives, management measures, and policy recommendations

R Chakrabortty, SC Pal, D Ruidas, P Roy, A Saha… - Water, 2023 - mdpi.com
Flood, a distinctive natural calamity, has occurred more frequently in the last few decades all
over the world, which is often an unexpected and inevitable natural hazard, but the losses …

Machine learning for naval architecture, ocean and marine engineering

JP Panda - Journal of Marine Science and Technology, 2023 - Springer
Abstract Machine learning (ML)-based techniques have found significant impact in many
fields of engineering and sciences, where data-sets are available from experiments and …

[HTML][HTML] Damage in rubble mound breakwaters. Part I: Historical review of damage models

Á Campos, C Castillo, R Molina-Sanchez - Journal of Marine Science …, 2020 - mdpi.com
The term “damage” in rubble mound breakwaters is usually related to the foremost failure
mode of this kind of coastal structures: their hydraulic instability. The characterization of the …

A methodology for data gap filling in wave records using Artificial Neural Networks

F Vieira, G Cavalcante, E Campos… - Applied Ocean …, 2020 - Elsevier
Wave measuring equipment are subject to malfunction that can be caused by various
reasons such as maintenance, navigation accidents, errors in communications and …

Novel time-efficient approach to calibrate VARANS-VOF models for simulation of wave interaction with porous structures using Artificial Neural Networks

F Vieira, F Taveira-Pinto, P Rosa-Santos - Ocean Engineering, 2021 - Elsevier
Numerical models are valuable tools to provide information on wave-structure interaction
processes that are difficult to measure in a physical model. The current level of accuracy of …

An application of machine learning algorithms on the prediction of the damage level of rubble-mound breakwaters

S Saha, S De, S Changdar - Journal of …, 2024 - asmedigitalcollection.asme.org
The stability analysis of breakwaters is very important to have a safe and economic design of
these coastal protective structures and the damage level is one of the most important …

Artificial neural networks applied to port operability assessment

I López, M López, G Iglesias - Ocean Engineering, 2015 - Elsevier
Waves are one of the main factors that can disturb port operations, from berthing to cargo
loading and unloading. Wave heights within port basins are typically assessed by means of …

Incident wave run-up prediction using the response surface methodology and neural networks

K Rehman, H Khan, YS Cho, SH Hong - … Environmental Research and …, 2022 - Springer
Submerged breakwaters (SBs) protect coastal areas from intense wave actions, such as
inundation and erosion, by controlling the wave run up. The effective regulation of wave run …