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Short-Term Wind Speed Prediction: Cnn-Lstm with Hyperparameter Tuning Using Modified Bat Algorithm

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.apenergy.2021.117766openalex-extracted

A review of wind speed and wind power forecasting with deep neural networks

inferredcites →https://doi.org/10.1016/j.apenergy.2023.121638openalex-extracted

COA-CNN-LSTM: Coati optimization algorithm-based hybrid deep learning model for PV/wind power forecasting in smart grid applications

inferredcites →https://doi.org/10.1016/j.oceaneng.2022.111352openalex-extracted

Wind speed prediction of unmanned sailboat based on CNN and LSTM hybrid neural network

inferredcites →https://doi.org/10.1016/j.suscom.2023.100869openalex-extracted

A CNN encoder decoder LSTM model for sustainable wind power predictive analytics

inferredcites →https://doi.org/10.1109/access.2020.2966268openalex-extracted

Short-Term Wind Speed Forecasting Based on Information of Neighboring Wind Farms

inferredcites →https://doi.org/10.1109/access.2021.3084536openalex-extracted

Short-Term Wind Speed Forecasting Based on Hybrid MODWT-ARIMA-Markov Model

inferredcites →https://doi.org/10.1109/jiot.2023.3286568openalex-extracted

Short-Term Wind Speed and Power Forecasting for Smart City Power Grid With a Hybrid Machine Learning Framework

inferredcites →https://doi.org/10.1109/tia.2021.3127145openalex-extracted

A Wind Speed Correction Method Based on Modified Hidden Markov Model for Enhancing Wind Power Forecast

inferredcites →https://doi.org/10.1109/tii.2020.3043451openalex-extracted

Hybrid Method Based on Random Convolution Nodes for Short-Term Wind Speed Forecasting

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