A review of deep learning for renewable energy forecasting

Evolution of Design Method Against Random Waves Statistical Properties and Spectral of Sea Waves Transformation and Deformation of Random Sea Waves Design of Breakwaters Design of Coastal Dikes and Seawalls Probabilistic Design of Harbor Facilities Harbor Tranquility and Vessel Mooring Hydraulic Model Tests with Random Waves Theoretical Description of Random Sea Waves Statistical Theory of Irregular Waves Techniques of Random Wave Analysis 2D Computation of Wave Transformation with Random Breaking and Nearshore Currents Statistical Analysis of Extreme Waves Prediction and Control of Beach Deformation Processes.

Random seas and design of maritime structures

Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM

Preparing the books to read every day is enjoyable for many people. However, there are still many people who also don't like reading. This is a problem. But, when you can support others to start reading, it will be better. One of the books that can be recommended for new readers is dynamics and modelling of ocean waves. This book is not kind of difficult book to read. It can be read and understand by the new readers.

Dynamics and Modelling of Ocean Waves

The aerodynamic characteristics of train/vehicles under cross winds depend on not only the shapes of the vehicles but also those of infrastructures. Accordingly three kinds of wind tunnel tests were made to evaluate the aerodynamic characteristics of typical configurations of the vehicles on typical configurations of infrastructures such as bridges and embankments. The main results obtained from the wind tunnel tests are summarized below. 1. The aerodynamic side force coefficient of the vehicle increases more as the thickness of the bridge girder becomes larger. It also increases more as the roof of the vehicle becomes edgier. 2. The aerodynamic characteristics of the vehicle on the embankment depend on the distribution of the boundary layer on the ground. The aerodynamic side force coefficient of the vehicle on a high embankment is larger than that on a low embankment.

Aerodynamic Characteristics of Train/Vehicles under Cross Winds

Dynamics of wind–rail vehicle–bridge systems

An improved Wavelet Transform using Singular Spectrum Analysis for wind speed forecasting based on Elman Neural Network

A novel framework for wind speed prediction based on recurrent neural networks and support vector machine

Comparative study on three new hybrid models using Elman Neural Network and Empirical Mode Decomposition based technologies improved by Singular Spectrum Analysis for hour-ahead wind speed forecasting

Yongle Li

Papers

Dynamics of wind–rail vehicle–bridge systems

An improved Wavelet Transform using Singular Spectrum Analysis for wind speed forecasting based on Elman Neural Network

A novel framework for wind speed prediction based on recurrent neural networks and support vector machine

Comparative study on three new hybrid models using Elman Neural Network and Empirical Mode Decomposition based technologies improved by Singular Spectrum Analysis for hour-ahead wind speed forecasting

Data mining-assisted short-term wind speed forecasting by wavelet packet decomposition and Elman neural network