Results 81 to 90 of about 83,069 (252)

Finite-Time Optimal Containment Control for Nonlinear Fractional-Order Multi-Agent Systems

IEEE Access
This paper investigates the finite-time optimal containment control problem for a class of fractional-order multi-agent systems with unknown nonlinear dynamics.
Xiru Wu, Yibo Zhao, Yi Lu
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

The effects of spatial stability and cue type on spatial learning : Implications for theories of parallel spatial memory systems [PDF]

, 2021
Some theories of spatial learning predict that associative rules apply under only limited circumstances. For example, learning based on a boundary has been claimed to be immune to cue competition effects because boundary information is the basis for the formation of a cognitive map, whilst landmark learning does not involve cognitive mapping.
Buckley, Matthew G., Austen, Joe M., Myles, Liam A. M., Smith, Shamus, Ihssen, Niklas, Lew, Adina, McGregor, Anthony   +6 more
openaire  

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Reconciling grokking with statistical learning theory through the lens of norm- and stability-based generalization bounds

Neurocomputing
In recent years, Artificial Intelligence, particularly Machine Learning, has achieved remarkable success in solving complex problems. However, this progress has also revealed the emergence of unexpected, poorly understood, and elusive phenomena that characterize the behavior of machine intelligence and learning processes.
Luca Oneto, Sandro Ridella, Simone Minisi, Andrea Coraddu, Davide Anguita   +4 more
openaire   +1 more source

Learning Control of Fixed-Wing Unmanned Aerial Vehicles Using Fuzzy Neural Networks

International Journal of Aerospace Engineering, 2017
A learning control strategy is preferred for the control and guidance of a fixed-wing unmanned aerial vehicle to deal with lack of modeling and flight uncertainties.
Erdal Kayacan, Mojtaba Ahmadieh Khanesar, Jaime Rubio-Hervas, Mahmut Reyhanoglu   +3 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

M-elite coevolutionary kinetic-molecular theory optimization algorithm

Tongxin xuebao, 2015
M-elite coevolutionary kinetic-molecular theory optimization algorithm (MECKMTOA) was proposed.MECKMTOA uses M elites to avoid misleading,improves the convergence precision by learning and collaboration among the elites,employs a new wave operator to ...
Chao-dong FAN, Jing ZHANG, Ling-zhi YI
doaj   +2 more sources