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Simulation and impact analysis of behavioral and socioeconomic dimensions of energy consumption
(
Elsevier
, 2022 , Article)
Human-oriented factors present unavoidable challenges and uncertainties in building energy strategic planning. The uncertainties escalate when the target society is not fully known to the decision-maker and can create ...
Accelerating the Change to Smart Societies- a Strategic Knowledge-Based Framework for Smart Energy Transition of Urban Communities
(
Frontiers Media
, 2022 , Article)
Urban communities differ in their social, economic, and environmental characteristics, as
well as in the approach to energy use. Dynamic energy use and available on-site resources
allow interaction with the surroundings ...
Spatial Assessment of COVID-19 First-Wave Mortality Risk in the Global South
(
Routledge
, 2022 , Article)
The coronavirus disease (COVID-19) that appeared in 2019 gave rise to a major global health crisis that is still topping global health, socioeconomic, and intervention program agendas. Although the outbreak of COVID-19 has ...
Spatial Associations between COVID-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman
(
Routledge
, 2022 , Article)
Migrants are among the groups most vulnerable to infection with viruses due to the social and economic
conditions in which they live. Therefore, spatial modeling of virus transmission among migrants is important
for ...
Spatial and temporal changes in electricity demand regulatory during pandemic periods: The case of COVID-19 in Doha, Qatar
(
Elsevier
, 2022 , Article)
The propagation of the pandemic times, especially during COVID-19, has caused millions of morbidity and mortality cases across the world, forcing people to change their lifestyles and governments to take different measures ...
The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar
(
Elsevier Ltd
, 2022 , Article)
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 demand forecasting accuracy in buildings in ...