Results 91 to 100 of about 9,444,467 (301)
Fault Classification of Reciprocating Compressor Based on Neural Networks and Support Vector Machines [PDF]
Reciprocating compressors play a major part in many industrial systems and faults occurring in them can degrade performance, consume additional energy, cause severe damage to the machine and possibly even system shut-down.
Gu, Fengshou +4 more
core +3 more sources
Support Vector Machines with Applications
Support vector machines (SVMs) appeared in the early nineties as optimal margin classifiers in the context of Vapnik's statistical learning theory. Since then SVMs have been successfully applied to real-world data analysis problems, often providing improved results compared with other techniques.
Moguerza, Javier M., Muñoz, Alberto
openaire +4 more sources
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno +19 more
wiley +1 more source
kernlab - An S4 package for kernel methods in R [PDF]
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 +10 more
core +1 more source
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong +10 more
wiley +1 more source
Interior Point Methods for Massive Support Vector Machines [PDF]
We investigate the use of interior point methods for solving quadratic programming problems with a small number of linear constraints where the quadratic term consists of a low-rank update to a positive semi-de nite matrix. Several formulations of the
Ferris, Michael, Munson, Todd
core
An Attribute Selection For Severity Level Determination According To The Support Vector Machine Classification Result [PDF]
Determination of bug severity level is needed in fixing bug. Actually, in bug-tracking system, there is around 14 attributes used for defining a bug. But, all this time we do not know which attributes are highly influential for this. In this research, a
Ghaluh Indah Permata , Sari
core +1 more source
Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck +10 more
wiley +1 more source
Benchmarking least squares support vector machine classifiers. [PDF]
In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a ( convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function
Suykens, Johan +7 more
core
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source

