Results 171 to 180 of about 1,003,903 (269)

Olympiad-level formal mathematical reasoning with reinforcement learning. [PDF]

open access: yesNature
Hubert T   +38 more
europepmc   +1 more source

Performance Investigation of Eco‐Friendly Refrigerant Mixtures as an Alternative to R134a in Vapour‐Compression Refrigeration System

open access: yesAsia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The growing impacts of climate change and energy scarcity demand environmentally sustainable refrigeration solutions. This study investigates eco‐friendly refrigerants (R152a, R290 and R600a) and their optimized ternary mixture as alternatives to R134a. Four blend compositions were analysed using experimental testing and REFPROP 10.0 modelling
M. Periyasamy, P. Senthilkumar
wiley   +1 more source

Advanced Investigation of the Elimination of Methylene Blue From Wastewater Using Activated Carbon–Copper Oxide Nanowires: New Perspectives With Statistical Physical Modeling

open access: yesAsia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT In this study, the actual route of methylene blue (MB) dye adsorption by using fabricated polyfunctional activated carbon–copper oxide nanowires (AC@CuO‐NWs) from bulky wastewater bodies has been investigated. To better understand the exact pathway of the adsorption process, a prominent statistical physics formalism or grand canonical ...
Abdellatif Sakly   +7 more
wiley   +1 more source

Wearable exoskeleton robot control using radial basis function‐based fixed‐time terminal sliding mode with prescribed performance

open access: yesAsian Journal of Control, EarlyView.
Abstract This paper tackles the problem of robust and accurate fixed‐time tracking in human–robot interaction and deals with uncertainties. This work introduces a control approach for a wearable exoskeleton designed specifically for rehabilitation tasks.
Mahmoud Abdallah   +4 more
wiley   +1 more source

Risk‐aware safe reinforcement learning for control of stochastic linear systems

open access: yesAsian Journal of Control, EarlyView.
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili   +2 more
wiley   +1 more source

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