Results 121 to 130 of about 2,420,336 (400)

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

NEW TECHNIQUES APPLIED IN ECONOMICS. ARTIFICIAL NEURAL NETWORK [PDF]

The present paper has the objective to inform the public regarding the use of new techniques for the modeling, simulate and forecast of system from different field of activity.
Constantin Ilie, Margareta Udrescu
core  

Artificial Neural Network Methods in Quantum Mechanics

, 1997
In a previous article we have shown how one can employ Artificial Neural Networks (ANNs) in order to solve non-homogeneous ordinary and partial differential equations.
A. Likas, Barron, Christodoulou, D.I. Fotiadis, Evangelakis, Flügge, Ford, Ford, Frost, Funahashi, Hornik, I.E. Lagaris, Kaluza, Kaneko, Kincaid, Lagaris, Papageorgiou, Saad, Saad, Saad, Williamson   +20 more
core   +4 more sources

Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science

Advanced Engineering Materials, EarlyView.
This manuscript presents advances in digital transformation within materials science and engineering, emphasizing the role of the MaterialDigital Initiative. By testing and applying concepts such as ontologies, knowledge graphs, and integrated workflows, it promotes semantic interoperability and data‐driven innovation. The article reviews collaborative
Bernd Bayerlein, Jörg Waitelonis, Henk Birkholz, Matthias Jung, Markus Schilling, Philipp v. Hartrott, Marian Bruns, Jörg Schaarschmidt, Kristian Beilke, Marcel Mutz, Vincent Nebel, Veit Königer, Lisa Beran, Tobias Kraus, Akhilesh Vyas, Lars Vogt, Moritz Blum, Basil Ell, Ya‐Fan Chen, Tina Waurischk, Akhil Thomas, Ali Riza Durmaz, Sahar Ben Hassine, Carina Fresemann, Gordian Dziwis, Hossein Beygi Nasrabadi, Thomas Hanke, Melissa Telong, Stephan Pirskawetz, Mohamed Kamal, Thomas Bjarsch, Ursula Pähler, Peter Hofmann, Mena Leemhuis, Özgür L. Özçep, Lars‐Peter Meyer, Birgit Skrotzki, Jörg Neugebauer, Wolfgang Wenzel, Harald Sack, Chris Eberl, Pedro Dolabella Portella, Tilmann Hickel, Lutz Mädler, Peter Gumbsch   +44 more
wiley   +1 more source

Practical Approach to Studying Evolutionary Methods for Setting Weight Coefficients of Artificial Neural Networks

Цифровая трансформация
The article describes the problems of developing neurocontrollers for controlling dynamic objects, including the complexity of forming training data sets. It is indicated that one of the known methods for training an artificial neural network controlling
D. O. Petrov
doaj   +1 more source

An application and modelling on the artificial neural network to the RHV Tube [PDF]

Revista Română de Informatică și Automatică
Artificial neural networks represent highly advanced and adaptable tools for addressing challenges, attributed to their capacity for learning through examples and forming generalisations.
Murat Eray KORKMAZ
doaj   +1 more source

The use of artificial neural networks in experimental data acquisition and aerodynamic design [PDF]

It is proposed that an artificial neural network be used to construct an intelligent data acquisition system. The artificial neural networks (ANN) model has a potential for replacing traditional procedures as well as for use in computational fluid ...
Meade, Andrew J., Jr.
core   +1 more source

Smart Rubber Extrusion Line Combining Multiple Sensor Techniques for AI‐Based Process Control

Advanced Engineering Materials, EarlyView.
This publication presents a digitalization approach for a laboratory rubber extrusion line, employing innovative measurement methods and artificial intelligence (AI)‐based process control. The results demonstrate that the measurement systems are capable of detecting changes in the process and extrudate quality.
Alexander Aschemann, Paul‐Felix Hagen, Simon Albers, Robin Rofallski, Sven Schwabe, Mohammed Dagher, Marco Lukas, Sebastian Leineweber, Benjamin Klie, Patrick Schneider, Hagen Bossemeyer, Lennart Hinz, Markus Kästner, Birger Reitz, Eduard Reithmeier, Thomas Luhmann, Hainer Wackerbarth, Ludger Overmeyer, Ulrich Giese   +18 more
wiley   +1 more source

Ontologies for FAIR Data in Additive Manufacturing: A Use Case‐Based Evaluation

Advanced Engineering Materials, EarlyView.
An ontology‐based approach for generating findable, accessible, interoperable, reusable data in additive manufacturing is explored, focusing on powder bed fusion. The article highlights the benefits of enhanced data findability and digital twin enablement, while addressing challenges like data integration complexity and the need for specialized ...
Thomas Bjarsch, Klaus Drechsler, Johannes Schilp   +2 more
wiley   +1 more source

Ontology‐Based Digital Infrastructure for Data‐Driven Glass Development

Advanced Engineering Materials, EarlyView.
This work addresses the inefficiencies in traditional glass development by implementing an ontology‐based digital infrastructure coupled with a high‐throughput robotic melting system. The approach integrates machine learning models, predictive tools, and a semantic database.
Ya‐Fan Chen, Felix Arendt, Hansjörg Bornhöft, Andréa S. S. de Camargo, Joachim Deubener, Andreas Diegeler, Shravya Gogula, Altair T. Contreras Jaimes, Sebastian Kempf, Martin Kilo, René Limbach, Ralf Müller, Rick Niebergall, Zhiwen Pan, Frank Puppe, Stefan Reinsch, Gerhard Schottner, Simon Stier, Tina Waurischk, Lothar Wondraczek, Marek Sierka   +20 more
wiley   +1 more source