Journal ArticleDOI
Significant wave height estimation using SVR algorithms and shadowing information from simulated and real measured X-band radar images of the sea surface
Sancho Salcedo-Sanz,J.C. Nieto Borge,L. Carro-Calvo,Lucas Cuadra,Katrin Hessner,Enrique Alexandre +5 more
TLDR
This paper shows that SVR can be successfully trained from simulation-based data, and shows the performance of the SVR in simulation data and how SVR outperforms alternative algorithms such as neural networks.About:
This article is published in Ocean Engineering.The article was published on 2015-06-01. It has received 66 citations till now. The article focuses on the topics: Sea state & Wave height.read more
Citations
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Journal ArticleDOI
Regional ocean wave height prediction using sequential learning neural networks
TL;DR: A study to predict the daily wave heights in different geographical regions using sequential learning algorithms, namely the Minimal Resource Allocation Network (MRAN) and the Growing and Pruning Radial Basis Function (GAP-RBF) network.
Journal ArticleDOI
Ocean Wind and Wave Measurements Using X-Band Marine Radar: A Comprehensive Review
TL;DR: The goal of this paper is to provide a comprehensive review of the state of the art algorithms for ocean wind and wave information extraction from X-band marine radar data.
Journal ArticleDOI
Computational intelligence in wave energy: Comprehensive review and case study
TL;DR: This paper reviews those used in wave energy applications, both in the resource estimation and in the design and control of wave energy converters, and illustrates the potential of hybridizing a Coral Reefs Optimization algorithm with an Extreme Learning Machine to tackle the problem of significant wave height reconstruction.
Journal ArticleDOI
Bayesian optimization of a hybrid system for robust ocean wave features prediction
TL;DR: It is shown that BO can be used to obtain the optimal parameters of a prediction system for problems related to ocean wave features prediction, and a hybrid Grouping Genetic Algorithm for attribute selection combined with an Extreme Learning Machine approach for prediction is proposed.
Journal ArticleDOI
Ocean wave height prediction using ensemble of Extreme Learning Machine
TL;DR: From this study, it is inferred that the Ens-ELM out performs ELM, Online Sequential ELM (OS- ELM), and Support Vector Regression (SVR) in the daily wave height prediction.
References
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Journal ArticleDOI
Comparison of Wave Spectra from Nautical Radar Images and Scalar Buoy Data
TL;DR: In this paper, the spectral analysis of ocean wave fields performed from nautical radar and buoy measurements is compared, and the comparison of different spectral parameters and scalar spectra from both sensors are presented.
Journal ArticleDOI
On the use of marine radar imagery for estimation of properties of the directional spectrum of the sea surface
TL;DR: In this paper, a unique radar system that digitizes and stores radar images eight bits deep directly related to the strength of the radar backscatter was deployed on the CSS Hudson during the Grand Banks ERS-1 SAR Wave Spectrum Validation Experiment cruise in November 1991.
Proceedings ArticleDOI
Estimation of surface wave spectra from nautical radar image sequences with a small azimuthal coverage
TL;DR: A method has been developed to estimate calibrated surface wave spectra from nautical radar image sequences based on the three-dimensional fast Fourier transformation of the spatio-temporal sea clutter pattern in the wavenumber-frequency domain.
Proceedings ArticleDOI
The analysis of sea surface dynamics using a dopplerized X-band radar
TL;DR: Common In-Situ Sensors acquire information about the dynamic sea surface punctual but continuously in time with high precision, and a method to deduce local wave spectra from measured Doppler velocities of the sea surface.
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