EOLO Develops Wave Energy Predicting Technique

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The UPV/EHU-University of the Basque Country has developed wave energy predictions for the Bay of Biscay by using a technique called random forests.

The EOLO group (UPV/EHU-University of the Basque Country) has developed various models for predicting the amount of wave energy for the Bay of Biscay, by using a technique called random forests.

“Random forests (RF) is an algorithm developed in recent years in the field of machine learning. The basis of RFs are the so-called ‘regression trees’, in which the input variables are regarded as roots and the output ones, the leaves. Hence the name ‘tree’. Random forest is a development of the regression trees which uses many trees (over a thousand, as a general rule) rather than just one, thus forming a forest,” explained Gabriel Ibarra of the EOLO group.

According to this researcher, the models developed by his group are more reliable than other ones already existing for predictions for the next three to sixteen hours. The EOLO models are based on a historical set of measurements that compare the energy levels of the waves at a given moment with each other and with those that are anticipated within a few hours. The measurements are made by means of buoys, five of which are in place in the Bay of Biscay, three off the Galician coast and two out at sea. The Spanish Ports Authority undertakes to maintain the buoys stationed in Galicia and the British meteorological service (MetOffice) the ones out at sea.

Source: offshoreWIND.biz