A growing world population and socio-economic development are at the root of an ever-
increasing energy demand throughout the world. Much of this demand is met by means of …

This study aims to assess the wind and wave spatio-temporal variability in the Persian Gulf
using localized ECMWF wind data and numerically modeled wave characteristics in a 31 …

This study aims to assess the wave energy at five coastal stations in the Gulf of Oman using
the time series of locally generated wind waves obtained by numerical modeling for 11 …

This study uses a machine learning algorithm, the bagged regression tree, to detect error
patterns within 24-h forecasts of significant wave height time series. The input to the …

Towed underwater vehicles are essential tools for providing safe access to the underwater
world with many applications including ocean research, naval operations, inspection and …

Excessive usage of fossil fuels and high emission of greenhouse gases have increased the
earth's temperature, and consequently have changed the patterns of natural phenomena …

Providing energy without unfavorable impacts on the environment is an important issue for
many countries. Wave energy is one of the renewable resources with high potential and low …

Estimating the extreme values of significant wave height (HS), generally described by the
HS return period TR function HS (TR) and by its confidence intervals, is a necessity in many …

The present work describes the implementation of a methodology based on the optimal
interpolation method for assimilating the altimeter data in a regional wave forecasting …

This study presents a novel machine learning-statistics framework combining radial basis
function neural networks (RBFNNs) with 2D geospatial interpolation for predicting the …