Genetic programming for real-time prediction of offshore wind

Abstract

Wind speed and its direction at two offshore locations along the west coast of India are predicted over future time-steps of 3 to 24 hrs based on a sequence past wind measurements made by floating buoys. This is done based on a relatively new soft computing tool using genetic programming. The attention of investigators has recently been drawn to the application of this approach that differs from the well-known technique of genetic algorithms in basic coding and application of genetic operators. Unlike most of the past works dealing with causative modeling or spatial correlations, this study explores the usefulness of genetic programming to carry out temporal regression. It is found that the resulting predictions of wind movements rival those made by an equivalent and more traditional artificial neural network and sometimes appear more attractive when multiple-error criteria were applied. The success of genetic programming as a modelling tool reported in this study may inspire similar applications in future in the problem domain of offshore engineering, and more research in the computing domain as well.