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 …

Time series forecasting of meteorological variables, such as the hourly air temperature, has
multiple benefits for industry, agriculture, and the environment. Due to the high accuracy …

The use of ground transportation in Indonesia, especially in major cities like Surabaya, has
experienced rapid growth. However, this increased usage has also led to a rise in traffic …

Time-ahead forecasting of renewable energy resources is essential for successful planning
and operation of renewable integrated micro grids. Numerous studies have focused on wind …

This study aims to conduct a sentiment analysis of conversations on social media Twitter
related to the Kanjuruhan Tragedy. Social media, especially Twitter, has become a …

The accurate prediction of small-scale three-dimensional wind fields is of great practical
significance for aviation safety, wind power generation, and related fields. This study …

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

As wind and photovoltaic energy become more prevalent, the optimization of power systems
is becoming increasingly crucial. The current state of research in renewable generation and …

This research focuses on accurately classifying pneumonia in children under the age of 5
using X-ray images, considering the challenge of an imbalanced dataset. A modified VGG …

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 …