
Environmental and Sustainability Indicators, Journal Year: 2024, Volume and Issue: unknown, P. 100517 - 100517
Published: Oct. 1, 2024
Language: Английский
Environmental and Sustainability Indicators, Journal Year: 2024, Volume and Issue: unknown, P. 100517 - 100517
Published: Oct. 1, 2024
Language: Английский
Energy Economics, Journal Year: 2024, Volume and Issue: 134, P. 107568 - 107568
Published: April 25, 2024
Language: Английский
Citations
14Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124558 - 124558
Published: Sept. 24, 2024
Language: Английский
Citations
8Applied Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 2843 - 2843
Published: March 6, 2025
The power-generation mix of future grids will be quite diversified with the ever-increasing share renewable energy technologies. Therefore, prediction electricity demand become crucial for resource optimization and grid stability. Machine learning- artificial intelligence-based methods are widely studied by researchers to tackle forecasting problem. However, since COVID-19 pandemic broke out, new challenges have surfaced research. In such a short amount time, significant shifts emerged in trends, making it apparent that possibility similar crises escalated complexity management problems. Motivated circumstances, this research presents an hour-ahead day-ahead benchmark using Deep Polynomial Neural Networks (DNN) Gene Expression Programming (GEP) methods. DNN GEP algorithms utilize on-site consumption data collected from university hospital over two years temporal granularity 15-minute intervals. Quarter-hourly meteorological, calendar, daily data, including cases cumulative divided four restriction levels, were also considered. These datasets used not only predict but investigate impact on hospital. nRMSE results show outperforms 8.27% 14.32%, respectively. For computational times, appears much faster than 82.83% 78.56% forecasting,
Language: Английский
Citations
0Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108369 - 108369
Published: March 1, 2025
Language: Английский
Citations
0Social Indicators Research, Journal Year: 2025, Volume and Issue: unknown
Published: April 11, 2025
Language: Английский
Citations
0Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124690 - 124690
Published: Oct. 24, 2024
Language: Английский
Citations
2Energy Policy, Journal Year: 2024, Volume and Issue: 191, P. 114175 - 114175
Published: May 26, 2024
Language: Английский
Citations
1Heliyon, Journal Year: 2024, Volume and Issue: 10(14), P. e34395 - e34395
Published: July 1, 2024
Language: Английский
Citations
1International Journal of Hygiene and Environmental Health, Journal Year: 2024, Volume and Issue: 261, P. 114429 - 114429
Published: July 23, 2024
Household air pollution is one of the leading causes death and disease globally. Emerging evidence elevated risk neonatal has been reported in Africa South Asia. However, on extent problem Latin America limited despite persistent use highly polluting cooking fuels. We assessed whether high-polluting household fuels increases compared to low-polluting Colombia.
Language: Английский
Citations
1Energy Strategy Reviews, Journal Year: 2024, Volume and Issue: 51, P. 101317 - 101317
Published: Jan. 1, 2024
The issues of energy accessibility and vulnerability have garnered significant attention in recent research. However, previous studies tended to emphasize access-based justice while neglecting vulnerability-based justice, particularly emergency scenarios. This study aims address this gap by examining the conceptual differences between two concepts through practical examples exploring profile energy-vulnerable individuals. In study, a dataset comprising 1650 buildings Los Angeles was selected. A spatial regression model employed investigate factors influencing use intensity (EUI) years 2019 2020, as well rate change EUI these years. analysis conducted within framework two-tier combining proposed article. results revealed that, considering impact COVID-19 pandemic on urban environment, more demographic types experienced adverse effects, indicating populations. Among groups, older adults were impacted adversely most, followed Asian population unemployed population. article compensates for shortcomings traditional perspectives confirms typology populations objectively. findings also confirm dependence heterogeneity impacts. will prompt reevaluation equity settings offer theoretical foundation policy decision-making.
Language: Английский
Citations
1