PEPNet: A barotropic primitive equations-based network for wind speed prediction-Reference-Cited by-同舟云学术

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PEPNet: A barotropic primitive equations-based network for wind speed prediction

Published:2023-10 Issue: Volume:167 Page:533-550
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Ye Rui,Zhang Baoquan,Li Xutao,Ye Yunming

Funder

Science, Technology and Innovation Commission of Shenzhen Municipality

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference34 articles.

1. PRO2SAT: Systematic probabilistic satisfiability logic in discrete hopfield neural network;Chen;Advances in Engineering Software,2023

2. Spatial–temporal short-term traffic flow prediction model based on dynamical-learning graph convolution mechanism;Chen;Information Sciences,2022

3. Forecastnet: A time-variant deep feed-forward neural network architecture for multi-step-ahead time-series forecasting;Dabrowski,2020

4. de Bézenac, Emmanuel, Pajot, Arthur, & Gallinari, Patrick (2018). Deep learning for physical processes: Incorporating prior scientific knowledge. In International conference on learning representations.

5. Multi-task learning for the prediction of wind power ramp events with deep neural networks;Dorado-Moreno;Neural Networks,2020

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1. A physics-informed learning algorithm in dynamic speed prediction method for series hybrid electric powertrain;Engineering Applications of Artificial Intelligence;2024-07

2. Instantaneous 2D extreme wind speed prediction using the novel Wind Gust Prediction Net based on purely convolutional neural mechanism;Engineering Applications of Computational Fluid Mechanics;2024-01-31

3. A Physics-Informed Learning Algorithm in Dynamic Speed Prediction Method for Series Hybrid Electric Powertrain;2024

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