Results 251 to 260 of about 1,342,874 (327)

A hierarchical fusion framework for vehicle to grid energy management using predictive intelligence and learning based pricing. [PDF]

Sci Rep
Nandagopal V, Bhaskar KB, Periakaruppan S, Raj VAC, Wong WK, Ng PK.   +5 more
europepmc   +1 more source

Reinforcement Learning-Based Control of Epidemics on Networks of Communities and Correctional Facilities. [PDF]

Med Decis Making
Weyant C, Lee S, Goldhaber-Fiebert JD.
europepmc   +1 more source

Effect of Contextual Interference and Differential Learning on Motor Skill Development and Motivation in Novice Basketball Players. [PDF]

Eur J Sport Sci
Shamshiri G, Fazeli D, Nazemzadegan G.
europepmc   +1 more source

Tight Glycemic Control Can Be Achieved in Adult ICU Patients Safely: Results From a 5-Year Single-Center Observational Study Using the STAR Glycemic Control Framework. [PDF]

J Diabetes Sci Technol
Seret M, Uyttendaele V, Chase JG, Shaw GM, Desaive T.   +4 more
europepmc   +1 more source

Stochastic choice drives variability in patch foraging decisions across species

Scholey EV, Apps MA, Humphries MD.
europepmc   +1 more source

A HLBDA, GA, and COA for optimal operation of distributed energy resources. [PDF]

PLoS One
Alhasnawi BN, Mlkat Almutoki SM, Hashim HK, Sadeq AM, Almousawi AQ, Jasim BH, Homod RZ, Hussain FFK, Al-Shareeda MA, Dočekalová A, Bureš V.   +10 more
europepmc   +1 more source

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Stochastic Optimal Control

Springer Texts in Business and Economics, 2021
In previous chapters we assumed that the state variables of the system are known with certainty. When the variables are outcomes of a random phenomenon, the state of the system is modeled as a stochastic process. Specifically, we now face a stochastic optimal control problem where the state of the system is represented by a controlled stochastic ...
Suresh P. Sethi
semanticscholar   +2 more sources

Stochastic Optimal Control Matching

Neural Information Processing Systems, 2023
Stochastic optimal control, which has the goal of driving the behavior of noisy systems, is broadly applicable in science, engineering and artificial intelligence.
Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen   +4 more
semanticscholar   +1 more source

Stationary distribution extinction and optimal control for the stochastic hepatitis B epidemic model with partial immunity

Physica Scripta, 2021
In this paper, a stochastic model (with random noise transmission) is designed. The model possesses substantial potential to describe the dynamical behavior of the Hepatitis B (HBV) virus and it’s control by applying the strategy of vaccinating an ...
Anwarud Din, Yongjin Li
semanticscholar   +1 more source

A Stochastic Gradient Descent Approach for Stochastic Optimal Control

East Asian Journal on Applied Mathematics, 2020
In this work, we introduce a stochastic gradient descent approach to solve the stochastic optimal control problem through stochastic maximum principle. The motivation that drives our method is the gradient of the cost functional in the stochastic optimal
Richard Archibald
semanticscholar   +1 more source