An Accurate Heave Signal Prediction Using Artificial Neural Network

Abstract

An accurate heave modeling is required for several applications, including hydrographic surveying. This paper proposes an adaptive heave signal modeling, which uses a neural network-based modelling. A recurrent neural network and three-layer feed forward neural network trained using the Levenberg-Marquardt learning algorithm is used for this purpose.  Computational results with five different datasets of real time heave are provided to validate the effectiveness of the artificial neural network-based model. It is shown that the new neural network-based model give a reliable heave model with excellent performance. Also, a comparison is made between the developed artificial neural network models and the autoregressive models. It is shown that the new artificial neural network-based model give the best performance results (i.e., the mean square error MSE).