Uncertainties in the application of artificial neural networks in ocean engineering

Artificial Neural Networks (ANNs) are becoming more popular to model ocean engineering problems. With the development of Artificial Intelligence, data-driven models are showing better behaviour and performance than the traditional models used in ocean engineering. However, the main limitation of ANNs models is the uncertainty associated to them and their “black box” nature. ANNs models present final results without any uncertainty or explanation and this limits enormously their applicability, especially in decision-making tasks. This research paper tries to deal with this problem. Given the exponential growth that artificial intelligence models are currently experiencing, it is necessary to address these limitations so that the field of ocean engineering does not fall behind. This is the final aim of this review research paper. A review of how ocean engineering studies have dealt with ANNs uncertainties has been carried out with the final objective of proposing new methods to deal with these uncertainties to make the application of this tool less constrained by its “black-box nature” and facilitate the expansion of these models in the field.