... able to harvest energy more efficiently than traditional single-DOF devices. As a step towards its optimisation and control, a power prediction model is developed, using the wave elevation and motions of the WEC to predict the power output of each PTO. The results show that using LSTM (Long-Short Term...

... prediction power-activation feed-forward neural network neural network real-time prediction international journal lstm experiment parametric roll motion cnn equation artificial intelligence frequency pfn motion engineering International Journal of Offshore and Polar Engineering (ISSN 1053...

... Memory (LSTM) model. There are several publications that proposed a hybrid approach for forecasting in geosciences and network training. Tsai et al. (2021) described a differential parameter learning framework to train models with complex nonlinear and nonstationary data. Tang et al. (2021) published...