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Application of neural networks and support vector machine for significant wave height prediction

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Berbic J., Ocvirk E., Carevic D., Loncar G.

Oceanologia

2017

tom 59

nr 3

For the purposes of planning and operation of maritime activities, information about wave height dynamics is of great importance. In the paper, real-time prediction of significant wave heights for the following 0.5–5.5 h is provided, using information from 3 or more time points. In the first stage, predictions are made by varying the quantity of significant wave heights from previous time points and various ways of using data are discussed. Afterwards, in the best model, according to the criteria of practicality and accuracy, the influence of wind is taken into account. Predictions are made using two machine learning methods – artificial neural networks (ANN) and support vector machine (SVM). The models were built using the built-in functions of software Weka, developed by Waikato University, New Zealand.

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Transformation of statistical and spectral wave periods crossing a smooth low-crested structure

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Carevic D., Loncar G., Prsic M.

Oceanologia

2012

tom 54

nr 1

We carried out experimental studies of a smooth submerged breakwater in a wave channel in order to study such a structure impacts on the changes of statistically and spectrally defined representative wave periods as waves cross it. We discuss the impact of relative submersion, i.e. the relationship between the breakwater crown submersion and the incoming significant wave length Rc/Ls−i, on the representative wave periods. The mean periods, estimated using statistical and spectral methods, were compared in front of and behind the breakwater: the two periods turned out to be identical. Based on the measurements of the spectral mean wave periods in front of and behind the breakwater, an empirical model is derived for estimating the reduction in mean spectral period for submerged and emerged smooth breakwaters.

Ograniczanie wyników

2 Oceanologia

2 Carevic D.

2 Loncar G.

1 Berbic J.

1 Ocvirk E.

1 Prsic M.

1 2017

1 2012

Wyniki wyszukiwania

Application of neural networks and support vector machine for significant wave height prediction

Transformation of statistical and spectral wave periods crossing a smooth low-crested structure