Forecasting of wave energy in Canary Islands based on Artificial Intelligence
Deivis Ávila, G.N. Marichal, Isidro Padrón, Ramón Quiza, Ángela Hernández
Abstract
In this work two mathematical models based on soft computing techniques for the forecasting of the wave energy in the Macaronesian region are exposed. The intelligent systems proposed for the wave energy prediction are Fuzzy Inference Systems (FIS) and Artificial Neural Networks (ANN). The models were implemented and validated thanks to the dataset of deep waters buoys belonging to Spain's State Ports, in several places near the Canary Islands. The buoys dataset covered a total period of 18 years. Once this research finished, it was possible to conclude that there is an excellent correspondence between annual wave energy predicted by ANN- and FIS-based models with respect to both buoys. These models constitute an effective tool to compute the wave power quickly and accurately at any point in oceanic deep waters, which allows for an optimal use of the dataset from the buoys even with only a few months of measurements.