Results 81 to 90 of about 212,484 (267)

An autoscalable approach to optimize energy consumption using smart meters data in serverless computing

Science and Technology for Energy Transition
Serverless computing has evolved as a prominent paradigm within cloud computing, providing on-demand resource provisioning and capabilities crucial to Science and Technology for Energy Transition (STET) applications.
Kaur Jasmine, Chana Inderveer, Bala Anju
doaj   +1 more source

Performance analysis of tabular and Fuzzy Q-learning under varying state and action space resolution [PDF]

International Journal of Electronics and Telecommunications
Reinforcement learning (RL) algorithms, such as Q-learning, are widely applied to control tasks involving continuous state spaces that require discretization or function approximation.
Roman Zajdel
doaj   +1 more source

Speedy Q-Learning.

, 2011
We introduce a new convergent variant of Q-learning, called speedy Q-learning, to address the problem of slow convergence in the standard form of the Q-learning algorithm. We prove a PAC bound on the performance of SQL, which shows that for an MDP with n state-action pairs and the discount factor γ only T = O(log(n)/(ε^2 (1 - γ)^4)) steps are required ...
Azar, Mohammad Gheshlaghi, Munos, Rémi, Ghavamzadeh, Mohammad, Kappen, Hilbert   +3 more
openaire   +3 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Improved Dynamic Q-Learning Algorithm to Solve the Lot-Streaming Flowshop Scheduling Problem with Equal-Size Sublots

Complex System Modeling and Simulation
The lot-streaming flowshop scheduling problem with equal-size sublots (ELFSP) is a significant extension of the classic flowshop scheduling problem, focusing on optimize makespan.
Ping Wang, Renato De Leone, Hongyan Sang
doaj   +1 more source

Zein‐Based Adhesives: Sustainable Extraction and Application in Bioadhesive Technologies

Advanced Engineering Materials, EarlyView.
Zein is extracted from corn gluten meal using a simple and scalable process with high yield (~90%). The resulting protein is applied in bioadhesives modified with Ca2+ and Fe3+ ions, exhibiting substrate‐dependent adhesion. The findings demonstrate competitive bonding performance and highlight the role of ionic interactions in tuning adhesion ...
Paula Bertolino Sanvezzo, Daniela Winsley Valereto Friozi, Vinícius de Oliveira, Marcia Cristina Branciforti   +3 more
wiley   +1 more source

Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

Complex System Modeling and Simulation
This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots (Bi-HFSP_CS). The objectives are to minimize the makespan and total energy consumption.
Benxue Lu, Kaizhou Gao, Peiyong Duan, Adam Slowik   +3 more
doaj   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Thermodynamic Pathways of Nonequilibrium Solidification in Wire‐Arc Additive Manufacturing Fe‐Based Multicomponent Alloy Structures

Advanced Engineering Materials, EarlyView.
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios, Anthony Gonzalez, Aleksander Aleman, Tyler Dolmetsch, Tanaji Paul, Arvind Agarwal   +5 more
wiley   +1 more source

A Reinforcement Learning Approach for Smart Farming [PDF]

Database Systems Journal, 2019
At a basic level, the aim of machine learning is to develop solutions for real-life engineering problems and to enhance the performance of different computers tasks in order to obtain an algorithm that is highly independent of human intervention.
Gabriela ENE
doaj