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 …

Wave energy is substantial as a resource, and its potential to significantly contribute to the
existing energy mix has been identified. However, the commercial utilization of wave energy …

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

This paper proposes a novel hybrid approach for feature selection in two different relevant
problems for marine energy applications: significant wave height (H m 0) and wave energy …

In this work, the levelised cost of energy (LCOE) from floating solar photovoltaics (PV) is
calculated and mapped in the Mediterranean Sea. A breakdown of the factors that influence …

In the last years, Bayesian optimization (BO) has emerged as a practical tool for high-quality
parameter selection in prediction systems. BO methods are useful for optimizing black-box …

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 …

Wind-generated wave energy is a renewable energy source that exhibits a huge potential
for sustainable growth. The design and deployment of wave energy converters at a given …

This paper analyzes the performance of three types of statistical models and a well-known
physics-based model for forecasting the wave energy flux. The forecasts are run over …

In this work two mathematical models based on soft computing techniques for the
forecasting of the wave energy in the Macaronesian region are exposed. The intelligent …