Machine Learning-Based Estimate of The Wind Speed Over Complex Terrain Using the LSTM Recurrent Neural Network
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Machine Learning-Based Estimate of The Wind Speed Over Complex Terrain Using the LSTM Recurrent Neural Network ; day:09 ; month:10 ; year:2023 ; pages:1-31 ; extent:31
Wind energy science discussions ; (09.10.2023), 1-31 (gesamt 31)
- Creator
-
Beu, Cassia Maria Leme
Landulfo, Eduardo
- DOI
-
10.5194/wes-2023-104
- URN
-
urn:nbn:de:101:1-2023101204303448244189
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:53 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Beu, Cassia Maria Leme
- Landulfo, Eduardo
Other Objects (12)
Machine-learning-based estimate of the wind speed over complex terrain using the long short-term memory (LSTM) recurrent neural network
A Deep Learning-Based Hybrid CNN-LSTM Model for Location-Aware Web Service Recommendation
Hybrid self-attention BiLSTM and incentive learning-based collaborative filtering for e-commerce recommendation systems
Hybrid CNN-LSTM Deep Learning for Track-Wise GNSS-R Ocean Wind Speed Retrieval
LSTM-in-LSTM for generating long descriptions of images
Control of Outdoor Robots at Higher Speeds on Challenging Terrain
Regional subsidence monitoring and prediction along high-speed railways based on PS-InSAR and LSTM
eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
ESTIMATE
A learning-based model predictive control scheme for injection speed tracking in injection molding process
Interpolation of quantile regression to estimate driver's risk of traffic accident based on excess speed
Wearable sensor and machine learning estimate tendon load and walking speed during immobilizing boot ambulation
Machine-learning-based estimate of the wind speed over complex terrain using the long short-term memory (LSTM) recurrent neural network
A Deep Learning-Based Hybrid CNN-LSTM Model for Location-Aware Web Service Recommendation
Hybrid self-attention BiLSTM and incentive learning-based collaborative filtering for e-commerce recommendation systems
Hybrid CNN-LSTM Deep Learning for Track-Wise GNSS-R Ocean Wind Speed Retrieval
LSTM-in-LSTM for generating long descriptions of images
Control of Outdoor Robots at Higher Speeds on Challenging Terrain
Regional subsidence monitoring and prediction along high-speed railways based on PS-InSAR and LSTM
eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
ESTIMATE
A learning-based model predictive control scheme for injection speed tracking in injection molding process
Interpolation of quantile regression to estimate driver's risk of traffic accident based on excess speed
Wearable sensor and machine learning estimate tendon load and walking speed during immobilizing boot ambulation
Machine-learning-based estimate of the wind speed over complex terrain using the long short-term memory (LSTM) recurrent neural network
A Deep Learning-Based Hybrid CNN-LSTM Model for Location-Aware Web Service Recommendation
Hybrid self-attention BiLSTM and incentive learning-based collaborative filtering for e-commerce recommendation systems
Hybrid CNN-LSTM Deep Learning for Track-Wise GNSS-R Ocean Wind Speed Retrieval
LSTM-in-LSTM for generating long descriptions of images
Control of Outdoor Robots at Higher Speeds on Challenging Terrain
Regional subsidence monitoring and prediction along high-speed railways based on PS-InSAR and LSTM
eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
ESTIMATE
A learning-based model predictive control scheme for injection speed tracking in injection molding process
Interpolation of quantile regression to estimate driver's risk of traffic accident based on excess speed