Machine Learning

Significant wave height prediction through artificial intelligent mode decomposition for wave energy management
The prediction of significant wave height (SWH) is crucial for managing wave energy. While many machine learning studies have focused …
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Intelligent fault diagnosis for triboelectric nanogenerators via a novel deep learning framework
Triboelectric nanogenerators (TENGs) provide a new approach to converting mechanical energy into electric power. Although many …
PDF DOI 中科院一区 Expert Systems with Applications
Lightweight Strawberry Instance Segmentation on Low-Power Devices for Picking Robots
Machine vision plays a great role in localizing strawberries in a complex orchard or greenhouse for picking robots. Due to the variety …
PDF DOI 中科院四区 Electronics
A data driven method for multi-step prediction of ship roll motion in high sea states
Ship roll motion in high sea states has large amplitudes and nonlinear dynamics, and its prediction is significant for operability, …
PDF DOI 中科院一区 Ocean Engineering
Surrogate models for twin-VAWT performance based on Kriging and artificial neural networks
The prediction of significant wave height (SWH) is crucial for managing wave energy. While many machine learning studies have focused …
PDF DOI 中科院一区 Ocean Engineering
Reinforcement learning-based close formation control for underactuated surface vehicle with prescribed performance and time-varying state constraints
This paper studies close formation control problem with prescribed performance and time-varying state constraints for a group of …
PDF DOI 中科院一区 Ocean Engineering
The mean wake model and its novel characteristic parameter of H-rotor VAWTs based on random forest method
Using the random forest (RF) algorithm, this study presented a key parameter to characterize the mean wake of H-rotor VAWTs while …
PDF DOI 中科院一区 Energy
2-D regional short-term wind speed forecast based on CNN-LSTM deep learning model
Short-term wind speed forecast is of great importance to wind farm regulation and its early warning. Previous studies mainly focused on …
PDF DOI 中科院一区 Energy Conversion and Management
Framework of airfoil max lift-to-drag ratio prediction using hybrid feature mining and Gaussian process regression
The maximum lift-to-drag coefficient of an airfoil directly affects the aerodynamic performance of wind turbine. Machine learning …
PDF DOI 中科院一区 Energy Conversion and Management
Short-term wind speed predicting framework based on EEMD-GA-LSTM method under large scaled wind history
Accurate short-term wind speed prediction is of great significance for early warning and regulation of wind farms. At present, the …
PDF DOI 中科院一区 Energy Conversion and Management