This research introduces a novel high-accuracy time-series forecasting method, namely the
Time Neural Network (TNN), which is based on a kernel filter and time attention mechanism …

Various supervised machine-learning algorithms for wind power forecasting have been
developed in recent years to manage wind power fluctuations and effectively correlate to …

With the advancement of prediction methods in the field of artificial intelligence, accurate
price predictions can effectively support financial portfolio selection. This paper proposes an …

This research explores the application of Long Short-Term Memory Systems (LSTMs) and
conventional machine learning calculations for prescient support in shrewd grids …

The black-box nature of neural networks is an obstacle to the adoption of systems based on
them, mainly due to a lack of understanding and trust by end users. Providing explanations …

Smart cities and IoT solutions are improving urban efficiency, resource optimization, and
public safety by using modern technologies. Deep residual Bi-LSTM (Long Short-Term …

In the field of meteorology, temperature forecasting is a significant task as it has been a key
factor in industrial, agricultural, renewable energy, and other sectors. High accuracy in …

Explainable AI (XAI) has received increased interest in research and practice, driven by
social, ethical and legal pressure for AI techniques that are capable of making decisions …

Abstract The Sultan Mahmud Badaruddin (SMB) II Palembang Meteorological Station is a
technical implementation unit (UPT) of the Meteorology, Climatology, and Geophysics …

Operational disruptions have a profound negative impact on supply chain companies'
business and financial performance. These companies counter such disruptions by …