Abstract Artificial Neural Networks (ANNs) are becoming more popular to model ocean
engineering problems. With the development of Artificial Intelligence, data-driven models …

Effective communication of disaster risks is crucial to provoking appropriate responses from
citizens and emergency operators. With recent advancement in Artificial Intelligence (AI) …

Waves in large lakes put coastal communities and vessels under threat, and accurate wave
predictions are needed for early warnings. While physics-based numerical wave models …

Accurate wave prediction can help avoid disasters. In this study, the significant wave height
(SWH) prediction performances of the recurrent neural network (RNN), long short-term …

This article explores the concepts of ocean wave multivariate multistep forecasting,
reconstruction and feature selection. We introduce recurrent neural network frameworks …

The physics-based approach is the most common framework for modelling ocean
engineering processes; however, in the last years data-driven models are becoming more …

The prediction of wave height and flux of energy is essential for most ocean engineering
applications. To simultaneously predict both wave parameters, this paper presents a novel …

Ocean surface wave environment due to its randomness has mostly been analyzed and
understood from a statistical way. Accurate and reliable wave prediction is the basic …

Computational intelligence-based ocean characteristics forecasting applications, such as
Significant Wave Height (SWH) prediction, are crucial for avoiding social and economic loss …

The wave energy sector has not reached a sufficient level of maturity for commercial
competitiveness, thus requiring further efforts towards optimizing existing technologies and …