- Modelling of Deep Learning|Based Downscaling for Wave ...🔍
- Deep learning approach for downscaling of significant wave height ...🔍
- Statistical Downscaling of Coastal Directional Wave Spectra Using ...🔍
- A deep learning model for downscaling the significant wave height ...🔍
- Downscaling a Large|Scale River Model Using Deep Learning🔍
- A Deep Learning–Based Approach for Empirical Modeling of Single ...🔍
- Deep learning for statistical downscaling of sea states🔍
- Machine Learning‐Based Wave Model With High Spatial Resolution ...🔍
Modelling of Deep Learning|Based Downscaling for Wave ...
Modelling of Deep Learning-Based Downscaling for Wave ... - MDPI
This paper proposes two main steps to develop machine learning-based downscaling for wave forecasting. The first step is to develop a wave dataset via wave ...
Deep learning approach for downscaling of significant wave height ...
In this study, we attempt to develop an improved deep learning model, namely Wave Super-Resolution Convolutional Neural Network (W_SRCNN), for high-resolution ...
Modelling of Deep Learning-Based Downscaling for Wave ...
A deep learning-based downscaling method for predicting a significant wave height in the coastal area from global wave forecasting data using the Long ...
(PDF) Modelling of Deep Learning-Based Downscaling for Wave ...
The deep learning method was trained using wave data obtained by a continuous numerical wave simulation using the SWAN wave model over a 20-year ...
GSDNet: A deep learning model for downscaling the significant ...
For the downscaling model, we used five variables with 1 h temporal resolution derived from MASNUM outputs as the input, which are the significant wave height ( ...
Modelling of Deep Learning-Based Downscaling for Wave ... - OUCI
This paper proposes a deep learning-based downscaling method for predicting a significant wave height in the coastal area from global wave forecasting data. We ...
Statistical Downscaling of Coastal Directional Wave Spectra Using ...
... learning-based method to downscale open ocean directional wave ... A Deep Learning–Based Approach for Empirical Modeling of Single-Point Wave.
A deep learning model for downscaling the significant wave height ...
Finer resolution is one of the development trends in ocean surface waves simulation and forecasting. However, high-resolution numerical models for ocean ...
Statistical Downscaling of Coastal Directional Wave Spectra Using ...
The results show that the deep learning approach can effectively and efficiently downscale coastal DWSs without relying on any predefined ...
Downscaling a Large-Scale River Model Using Deep Learning
This study proposes a physics-informed machine learning model to simulate the downscaled flow at the subgrid scale. For the special case of ...
A Deep Learning–Based Approach for Empirical Modeling of Single ...
The wave spectrum data of ERA5 consist of 24 directional bins with 15° spacing and 30 frequency bins increasing exponentially from 0.0345 to 0.5473 Hz. This ...
Deep learning for statistical downscaling of sea states - ASCMO
To consider the spatiotemporal relationship between wind and waves, more complex architectures, such as 3D-CNN or long short-term memory (LSTM) ...
GSDNet: A deep learning model for downscaling the significant ...
Finer resolution is one of the development trends in ocean surface waves simulation and forecasting. However, high-resolution numerical ...
Machine Learning‐Based Wave Model With High Spatial Resolution ...
A high-resolution wave model is crucial for accurate modeling of sediment and organic material transports, but its computational costs ...
Statistical downscaling of coastal directional wave spectra using ...
The results show that the deep learning approach can effectively and efficiently downscale coastal DWSs without relying on any predefined spectral shapes, ...
Modelling of Deep Learning-Based Downscaling for Wave ...
Subject Terms: *DEEP learning *DOWNSCALING (Climatology) *FORECASTING *THEORY of wave motion ; Keywords: BiLSTM downscaling. LSTM wave forecasting. Abstract ...
Deep Learning for Daily Precipitation and Temperature Downscaling
Coarse resolution data sets (such as climate reanalysis, numerical weather predictions, satellite products, and simulations of general circulation models) are ...
Deep learning for statistical downscaling of sea states
A convolutional neural network (CNN)-type model for the prediction of significant wave height from wind fields in the Bay of Biscay is presented and the ...
Wave Downscaling Approach with TCN model, Case Study in ...
Traditional approaches for wave downscaling are usually obtained by performing nested simulations on a high-resolution local grid from global ...
An improved deep learning procedure for statistical downscaling of ...
2.3. Data preprocessing and statistical downscaling based on the CNN model ... Deep learning (DL) is an improved version of an artificial neural ...