Forecasting the electrical load is essential in power system design and growth. It is critical
from both a technical and a financial standpoint as it improves the power system …

Accurately forecasting stock prices helps investors decide when and where to invest.
However, the dynamic, non-linear, complex and chaotic nature of the stock market makes …

Mitigating city carbon emissions in major emitting economies is vital for sustainable
development. This study exploits the complex interactions among major sources of …

This study proposes an effective wind speed forecasting model combining a data processing
strategy, neural network predictor, and parameter optimization method.(a) Variational mode …

Forecasting stock movements is a crucial research endeavor in finance, aiding traders in
making informed decisions for enhanced profitability. Utilizing actual stock prices and …

Global solar radiation (GSR) prediction capability with a reliable model and high accuracy is
crucial for comprehending hydrological and meteorological systems. It is vital for the …

In the domain of dynamic graph representation learning (DGRL), capturing the temporal
evolution within real-world networks is of paramount importance. Spiking Neural Networks …

This paper aims to enhance the understanding and prediction of stock market behavior
during unexpected events like the COVID-19 pandemic, with a specific focus on the role of …

In recent years, wave energy has gained attention for its sustainability and cleanliness. As
one of the most important parameters of wave energy, significant wave height (SWH) is …

In recent years, the adverse effects of climate change have increased rapidly worldwide,
driving countries to transition to clean energy sources such as solar and wind. However …