Results 81 to 90 of about 108,016 (310)

Support vector machines in structural engineering: a review

Journal of Civil Engineering and Management, 2015
Recent development in data processing systems had directed study and research of engineering towards the creation of intelligent systems to evolve models for a wide range of engineering problems.
Abdulkadir Çevik, Ahmet Emin Kurtoğlu, Mahmut Bilgehan, Mehmet Eren Gülşan, Hasan M. Albegmprli   +4 more
doaj   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Analysis of support vector machines [PDF]

Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, 2003
We compare L1 and L2 soft margin support vector machines from the standpoint of positive definiteness, the number of support vectors, and uniqueness and degeneracy of solutions. Since the Hessian matrix of L2 SVM is positive definite, the number of support vectors for L2 SVM is larger than or equal to the number of L1 SVM.
openaire   +1 more source

Support vector machines for optimal channel decoding

EURASIP Journal on Wireless Communications and Networking
In this work, we investigate channel decoding techniques based on machine learning, and more specifically, on support vector machines (SVMs). Existing SVM-based decoders suffer from a scalability problem, characterized by the exponential growth of both ...
Gastón De Boni Rovella, Meryem Benammar, Tarik Benaddi, Hugo Méric   +3 more
doaj   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Data Mining via Support Vector Machines

, 2001
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various elds. Much more recently, SVMs have become the tool of choice for problems arising in data classi - cation and mining.
Mangasarian, Olvi
core  

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

A Survey on Potential of the Support Vector Machines in Solving Classification and Regression Problems [PDF]

Kernel methods and support vector machines have become the most popular learning from examples paradigms. Several areas of application research make use of SVM approaches as for instance hand written character recognition, text categorization, face ...
Catalina COCIANU, Luminita STATE, Doina FUSARU   +2 more
core   +1 more source

Slip Localization Intensification Mediated by Grain Boundary Sliding in a Polycrystalline Nickel‐Based Superalloy

Advanced Engineering Materials, EarlyView.
The temperature dependence of fatigue behavior in nickel‐based superalloys is investigated through high‐resolution measurements of plastic localization. While increasing temperature reduces localization and enhances fatigue performance in René 88DT, Inconel 718 exhibits a sharp degradation at intermediate temperature due to intensified slip ...
M. Calvat, D. Anjaria, I. Woo, C. Bean, D. Texier, J. C. Stinville   +5 more
wiley   +1 more source

Support Vector Committee machines [PDF]

, 2000
This paper proposes a mathematical programming framework for combining SVMs with possibly different kernels. Compared to single SVMs, the advantage of this approach is twofold: it creates SVMs with local domains of expertise leading to local enlargements of the margin, and it allows the use of simple linear kernels combined with a fixed boolean ...
Martinez, Dominique, Millerioux, Gilles
openaire   +1 more source