The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …

Carbon footprint (CF) estimation has emerged as an integral tool for greenhouse gas (GHG)
management, providing direction for emission reduction strategies and verification …

Accurately modeling and forecasting electricity consumption remains a challenging task due
to the large number of the statistical properties that characterize this time series such as …

The aim of this study was to investigate the possible influences of the operation of the new
Doha Metro on the travel mode choice behavior in Doha City, Qatar. Revealed preference …

This study investigated the impact of economic growth, electricity consumption, energy
consumption, and the crop production index on environmental quality in Qatar by …

The goal of this study is to use machine-learning (ML) techniques and empirical big data to
examine the influence of the COVID-19 pandemic on electricity usage and electricity …

Ensuring sustainable water and electricity consumption in urban residential buildings is a
growing challenge worldwide, particularly in rapidly develo** regions with harsh climates …

The process of estimating the carbon footprint (CF) has become a key method for managing
greenhouse gas (GHG) emissions, guiding strategies for emission reduction and validating …

The carbon footprint (CF) linked to electricity consumption in buildings has become a
significant environmental issue because of its significant role in greenhouse gas emissions …

In previous studies, geometrical aspects of the buildings have been mainly considered in
designing of the models, while the impacts of vegetation distribution have not been taken …