This paper proposes using optimised deep learning neural networks to forecast the wave energy flux, and other wave parameters. In particular, we use moth-flame optimisation as the central decision-making unit to configure the deep neural network structure and the proper input data selection. Besides...
With the advent of 'Deep Learning', Artificial Intelligence (AI) has attracted the attention of researchers in various fields, including ocean engineering. This paper applies AI to forecasting a water-surface wave train. Recurrent neural networks (RNN) are used to forecast both actual wave trains...
The recurrent neural network-long short-term memory (RNN-LSTM) model is adopted in the deep learning analytics. Currently, this system is capable of daily providing the next 4-day wind field forecast and the next 7-day wave and current field forecast. Through the testing, it is found that...
展开 关键词: deep learning wave energy wind energy long short-term memory EMPIRICAL MODE DECOMPOSITION NEURAL-NETWORK BELIEF NETWORK SPEED OPTIMIZATION REGRESSION MULTISTEP ALGORITHM STRATEGY FORECAST DOI: 10.3390/en15041510 年份: 2022 收藏 引用 批量引用 报错 分享 全部...
Wave attenuation (by ice) formulas based on wave heights are effective in both deep oceans and shallow lakes. Plain Language Summary Wave models are used to provide forecast guidance on wave conditions throughout the Great Lakes, improving safety for navigation and recreation. In the winter, wave...
It is critical to have a useful first-cut forecast on time series problems to provide a lower-bound on skill before moving on to more sophisticated methods. This is to ensure we are not wasting time on models or datasets that are not predictive. It is common to use a persistence or a ...
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In this study, we developed a deep learning model based ... Y Zeng,J Ma,X Chen,... - 《Comput Informatics》 被引量: 0发表: 2022年 XWaveNet: Enabling uncertainty quantification in short-term ocean wave height forecasts and extreme event prediction To aid accurate short-term forecast of ...
Wave height forecast method with uncertainty quantification based on Gaussian process regression 2024, Journal of Hydrodynamics A Frequency Domain Kernel Function-Based Manifold Dimensionality Reduction and Its Application for Graph-Based Semi-Supervised Classification ...
In this respect, the extension of the forecast horizon will permit long-haul routes and multi-port vessel routes to be addressed. As a function of the wave conditions, SIMROUTE may provide a limited extension to the benefits of the optimized route and the minimum distance route. The results ...