This paper investigates a deep learning‐based wind‐forecasting model to establish an
accurate forecasting model which can support the increasing growth of wind power …

The aim of this work is to find the most efficient and suitable input features to be selected for
forecasting monthly wind energy accurately. Machine learning is employed for a modular …

This paper proposes the prediction model of wind speed and direction using convolutional
neural network-long short-term memory (CNN-LSTM). The proposed prediction model …

Deep learning (DL) systems have been widely utilized across various domains. However,
the evolution of DL systems can result in regression faults. In addition to the evolution of DL …

This paper presents the prediction system of wind speed and direction one hour ahead
using encoding-forecasting network with convolutional long short-term memory …

Penelitian ini bertujuan untuk mengembangkan model deep learning yang mendeteksi jenis
sampah sehingga sampah dapat dipisahkan dan didaur ulang dengan sistem computer …

This paper proposed deep learning to create an accurate forecasting system that uses a
deep convolutional long short-term memory (DCLSTM) for forecasting wind speed and …

This paper serves forecast wind speed and direction using a convolutional neural network-
deep convolutional long short term memory (CNN-DConvLSTM). The forecasting model …

Makalah ini mengusulkan sistem prediksi kecepatan dan arah angin menggunakan sistem
bidirectional long short-term memory (BILSTM) untuk periode prediksi satu jam ke depan …

Dalam beberapa tahun terakhir, layanan streaming musik seperti Spotify telah menjadi
sangat populer. Spotify menyediakan jutaan lagu yang dapat diakses oleh pengguna …