Results 141 to 150 of about 184,437 (258)

Federated reinforcement learning with constrained markov decision processes and graph neural networks for fair and grid-constrained coordination of large-scale electric vehicle charging networks. [PDF]

Sci Rep
Zhou L, Huo D, Chen J, Bo B, Li H.
europepmc   +1 more source

An Investigation of Key Symptoms That Account for the Early Response Effect During Psychological Therapy for Eating Disorders

European Eating Disorders Review, EarlyView.
ABSTRACT Objective The early response effect, defined as a reliable symptomatic improvement during the initial phase of treatment, is the most robust predictor of recovery following eating disorder treatment. This study aimed to investigate which symptom domains mostly influence the early response effect. Methods Data from N = 232 adult patients (90.8%
Ammara Imtiaz, Caroline Bell, Glenn Waller, Jaime Delgadillo   +3 more
wiley   +1 more source

Revolutionizing load harmony in edge computing networks with probabilistic cellular automata and Markov decision processes. [PDF]

Sci Rep
Sahu D, Nidhi, Chaturvedi R, Prakash S, Yang T, Rathore RS, Wang L, Tahir S, Bakhsh ST.   +8 more
europepmc   +1 more source

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

Energy Science &Engineering, EarlyView.
Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga, Subhasish Deb, Kshetrimayum Robert Singh, Subir Datta, Ahmet Onen, Taha Selim Ustun, Jaesung Jung   +6 more
wiley   +1 more source

Intelligent Control Framework of District Heating Systems Considering Waste Heat Utilization in Data Centers

Energy Science &Engineering, EarlyView.
A deep reinforcement learning–based control architecture is proposed to coordinate heat pumps, thermal storage, renewable energy, and demand response in data center waste heat recovery systems. The agent learns optimal control actions from system states and reward feedback to achieve electrical–thermal co‐optimization under realistic operational ...
Rendong Shen, Ruifan Zheng, Shengyuan Zhong, Lei Gu, Dongfang Yang, Jun Zhao   +5 more
wiley   +1 more source

A Rapid Post‐Disaster Restoration Method for Networked Microgrids Based on Adaptive Quantum Particle Swarm Optimization

Energy Science &Engineering, EarlyView.
To enhance the power restoration speed of networked microgrids (NMGs) after extreme natural disasters and reduce the power outage of the system, this paper proposes a rapid post‐disaster restoration method for NMGs based co‐optimization of fault repair and load restoration.
Yunfan Zhang, Qiang Li, Jun Zhang, Chaohuang Xu   +3 more
wiley   +1 more source

Learning to maximize reward rate: a model based on semi-Markov decision processes. [PDF]

Front Neurosci, 2014
Khodadadi A, Fakhari P, Busemeyer JR.
europepmc   +1 more source

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, EarlyView.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Regime‐Dependent Nowcasting of the Austrian Economy

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast and forecast economic activity in Austria, namely, real gross domestic product (GDP), consumption, and investment, which are available at a quarterly frequency, using a preselected number of monthly indicators based on a combination of statistical procedures.
Jaroslava Hlouskova, Ines Fortin
wiley   +1 more source