Electricity market liberalization and the absence of cost-efficient energy storage
technologies have led to the transformation of state-owned electricity companies into …

The evolution of electricity markets has led to increasingly complex energy trading dynamics
and the integration of renewable energy sources as well as the influence of several external …

The study compares the prediction performance of alternative machine learning algorithms
and time series econometric models for daily Turkish electricity prices and defines the …

With the deepening of China's electricity spot market construction, spot market price
prediction is the basis for making reasonable quotation strategies. This paper proposes a …

Electricity market forecasting is very useful for the different actors involved in the energy
sector to plan both the supply chain and market operation. Nowadays, energy demand data …

The development of a stable, safe, secure and sustainable energy future is a challenge for
all countries these days. In terms of electricity price, its volatile nature makes its prediction a …

Earth observation imaging technologies, particularly multispectral sensors, produce
extensive high-dimensional data over time, thus offering a wealth of information on global …

The generalization in the use of virtualization in the upcoming generation of cellular
networks involves new paradigms and approaches for their management. The correct …

Forecasting techniques for renewable energy offer useful information about the anticipated
changes in the energy that will be generated in the near future. Besides, the emergence of …

Sepsis is a life-threatening condition whose early recognition is key to improving outcomes
for patients in intensive care units (ICUs). Artificial intelligence can play a crucial role in …