Results 111 to 120 of about 350,996 (311)

Support Vector Machine and Generalization

Journal of Advanced Computational Intelligence and Intelligent Informatics, 2004
The support vector machine (SVM) has been extended to build up nonlinear classifiers using the kernel trick. As a learning model, it has the best recognition performance among the many methods currently known because it is devised to obtain high performance for unlearned data.
openaire   +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

Biased support vector machine and weighted-smote in handling class imbalance problem

IJAIN (International Journal of Advances in Intelligent Informatics), 2018
Class imbalance occurs when instances in a class are much higher than in other classes. This machine learning major problem can affect the predicted accuracy.
Hartono Hartono, Opim Salim Sitompul, Tulus Tulus, Erna Budhiarti Nababan   +3 more
doaj   +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

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

Forecasting of Short-term Power Load Based on Improved PSO Algorithm and LS-SVM

Gong-kuang zidonghua, 2012
For problems of small samples, nonlinear, high dimensions and the local minimum of electric power load, a modeling method based on the least square support vector machine was proposed to forecast short-term power load by taking historical load ...
PAN Lei, LI Li-juan, DING Ting-ting, LIU Dui   +3 more
doaj  

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

kernlab - An S4 package for kernel methods in R [PDF]

, 2004
kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 object model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels),
Zeileis, Achim, Kurt Hornik, Smola, Alex, Alexandros Smola, Achim Zeileis, Smola, Alexandros, Karatzoglou, Alexandros, Hornik, Kurt, Alexandros Karatzoglou, Technische Universität Wien, Alex Smola   +10 more
core   +1 more source

Fatigue Crack Initiation and Growth in Nanocrystalline Ni at Multiple Length‐Scales

Advanced Engineering Materials, EarlyView.
Overview of miniaturized in situ SEM fatigue setup and resultant fatigue crack growth data for nanocrystalline Ni. The presented study focuses on the analysis of fatigue crack growth rate (FCGR) in focused ion beam‐notched microcantilevers prepared from nanocrystalline (NC) Ni as a model material.
Igor Moravcik, Alexander Jelinek, Markus Alfreider, Jutta Luksch, Anton Hohenwarter, Florian Schaefer, Christian Motz, Daniel Kiener   +7 more
wiley   +1 more source

Traffic fatalities prediction using support vector machine with hybrid particle swarm optimization

Journal of Algorithms & Computational Technology, 2018
Road traffic safety is essential, therefore in order to predict traffic fatalities effectively and promote the harmonious development of transportation, a traffic fatalities prediction model based on support vector machine is established in this paper ...
Xiaoning Gu, Ting Li, Yonghui Wang, Liu Zhang, Yitian Wang, Jinbao Yao   +5 more
doaj   +1 more source