Electricity load forecasting has been attracting research and industry attention because of its
importance for energy management, infrastructure planning, and budgeting. In recent years …

Just after the Indian government issued the first lockdown rule to cope with the increasing
number of COVID-19 cases in March 2020, the energy consumption in India plummeted …

Accurate energy consumption prediction is the basis of predictive control for heating,
ventilation and air conditioning (HVAC) systems. Data-driven models are widely used for …

Abstract Machine learning-based geospatial applications offer unique opportunities for
environmental monitoring due to domains and scales adaptability and computational …

Data-driven modeling emerges as a promising approach to predicting building electricity
consumption and facilitating building energy management. However, the majority of the …

The main objective of this research was to test the effect of oil prices, renewable and non-
renewable energy consumption, and economic growth on Turkey's carbon emissions by …

It is recognized that the performance of any prediction model is a function of several factors.
One of the most significant factors is the adopted preprocessing techniques. In other words …

Time series forecasting models are gaining traction in many real-world domains as valuable
decision support tools. Stock market analysis is a challenging domain, characterized by a …

The increasing presence of renewable energy plants has created new challenges such as
grid integration, load balancing and energy trading, making it fundamental to provide …

This comprehensive literature review examines the key concepts of entropy generation
minimization and its significant impact on the advancement of renewable energy systems …