Zobrazeno 1 - 10
of 464
pro vyhledávání: '"Zamzam Ahmed"'
High penetration from volatile renewable energy resources in the grid and the varying nature of loads raise the need for frequent line switching to ensure the efficient operation of electrical distribution networks. Operators must ensure maximum load
Externí odkaz:
http://arxiv.org/abs/2411.11791
Publikováno v:
BMC Health Services Research, Vol 18, Iss 1, Pp 1-11 (2018)
Abstract Background A previous census of electronic prescribing (EP) systems in England showed that more than half of hospitals with EP reported more than one EP system within the same hospital. Our objectives were to describe the rationale for havin
Externí odkaz:
https://doaj.org/article/9c9b077002d8483982d5b8e95b2ddd5c
In the context of managing distributed energy resources (DERs) within distribution networks (DNs), this work focuses on the task of developing local controllers. We propose an unsupervised learning framework to train functions that can closely approx
Externí odkaz:
http://arxiv.org/abs/2403.11068
The increasing number of wildfires in recent years consistently challenges the safe and reliable operations of power systems. To prevent power lines and other electrical components from causing wildfires under extreme conditions, electric utilities o
Externí odkaz:
http://arxiv.org/abs/2402.04444
Publikováno v:
PLoS ONE, Vol 14, Iss 5, p e0217023 (2019)
Medical errors are of economic importance and can contribute to serious adverse events for patients. Medical errors refer to preventable events resulting from healthcare interactions, whether these events harm the patient or not. In Kuwait, there is
Externí odkaz:
https://doaj.org/article/b95fc547ce5d4441a9770b779332e8a2
This paper tackles the problem of solving stochastic optimization problems with a decision-dependent distribution in the setting of stochastic strongly-monotone games and when the distributional dependence is unknown. A two-stage approach is proposed
Externí odkaz:
http://arxiv.org/abs/2312.17471
This research explores the joint expansion planning of power and water distribution networks, which exhibit interdependence at various levels. We specifically focus on the dependency arising from the power consumption of pumps and develop models to s
Externí odkaz:
http://arxiv.org/abs/2312.10224
In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced by multiple timescales, are non-stationary. Learning non-stationary po
Externí odkaz:
http://arxiv.org/abs/2307.08794
As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many electric utilities de-energize power lines to prevent electric faults and
Externí odkaz:
http://arxiv.org/abs/2306.03325
Constrained multiagent reinforcement learning (C-MARL) is gaining importance as MARL algorithms find new applications in real-world systems ranging from energy systems to drone swarms. Most C-MARL algorithms use a primal-dual approach to enforce cons
Externí odkaz:
http://arxiv.org/abs/2211.16069