Smart cities are an innovative concept for managing metropolitan areas to increase their
residents' sustainability and quality of life. This article examines the management and …

The forecast of electricity demand has been a recurrent research topic for decades, due to its
economical and strategic relevance. Several Machine Learning (ML) techniques have …

Many businesses and industries nowadays rely on large quantities of time series data
making time series forecasting an important research area. Global forecasting models that …

Effective electricity consumption forecasting is extremely significant for enterprises' electricity
planning which can provide data support for production decision, thus improving the level of …

Predicting energy consumption in buildings plays an important part in the process of digital
transformation of the built environment, and for understanding the potential for energy …

Recent trends in research reveal evolution of hybrid machine learning models based on
deep neural networks and nature inspired computing. In this paper, a combined model of …

This article is a methodical attempt to understand the factors that influence energy
consumption in households in the mountainous settlement of Metsovo, Greece. So far, most …

Energy consumption forecasting is an operation of predicting the future energy consumption
of electrical systems using previous or historical data. The Long Short-term Memory (LSTM) …

With the rapid increase in the world's human population and the advancement of
technology, energy utilization has substantially increased. To sustain a stable stream of …

Over the last few decades, electricity consumption has been increasing at an exponential
rate. The power distributors are being put under a lot of strain as a result of such rise. The …