Genetic Programming for Sea Level Predictions in an Island Environment

Abstract

Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP) and artificial neural networks (ANNs) were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling) Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.