Results 81 to 90 of about 3,022,789 (295)
Firat University Journal of Experimental and Computational Engineering, 2023 Traditional statistical regression models for predicting casualty severity have fundamental limitations. Machine learning algorithms for classifications have started to be applied in severity analysis in order to relax the assumptions and provide better ...
Nurten Akgün
doaj
Classification of Autism Spectrum Disorder Using Random Support Vector Machine Cluster
Frontiers in Genetics, 2018 Autism spectrum disorder (ASD) is mainly reflected in the communication and language barriers, difficulties in social communication, and it is a kind of neurological developmental disorder.
Xia-an Bi +4 more
doaj +1 more source
, 2011 This paper proposes a new approach based on Simple Random Sampling (SRS) technique with Least Square Support Vector Machine (LS-SVM) to classify two-class of electroencephalogram (EEG) signals.
Wen, Peng, Li, Yan
core +1 more source
Some Deterministic and Random Vector Equilibrium Problems [PDF]
, 2002 In this paper, some generalized concepts about semicontinuity and convexity for vector-valued bifunctions are introduced. A new existence theorem for vector equilibrium problems is proved.
Kalmoun, El Mostafa
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Annals of Clinical and Translational Neurology, EarlyView.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
Real eigenvalue/vector distributions of random real antisymmetric tensors
Journal of High Energy PhysicsReal eigenpairs of a real antisymmetric tensor of order p and dimension N can be defined as pairs of a real eigenvalue and p orthonormal N-dimensional real eigenvectors.
Nicolas Delporte +3 more
doaj +1 more source
Vector Stochastic Differential Equations Used to Electrical Networks with Random Parameters
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems, 2013 In this paper we present an application of the Itô stochastic calculus to the problem of modelling RLC electrical circuits. The deterministic model of the circuit is replaced by a stochastic model by adding a noise term to various parameters of the ...
Edita Kolářová, Lubomír Brančík
doaj +1 more source
On Infinitely Divisible Random Vectors
The Annals of Mathematical Statistics, 1957 A normally distributed random vector $X$ is well known to be representable by $A \cdot Y$ (in the sense of having identical distributions), where $A$ is a matrix of constants and $Y$ is a random vector whose component random variables are independent. A necessary and sufficient condition for any infinitely divisible random vector to be so representable
Dwass, Meyer, Teicher, Henry
openaire +3 more sources
Depth functions based on a number of observations of a random vector [PDF]
We present two statistical depth functions given in terms of the random variable defined as the minimum number of observations of a random vector that are needed to include a fixed given point in their convex hull.
Ignacio Cascos
core
Arthritis Care &Research, EarlyView.Objective Studies of damage accrual in patients with systemic lupus erythematosus (SLE) show associations with disease activity measured by the SLE Disease Activity Index 2000 (SLEDAI‐2K), but these associations are imperfect. SLEDAI scores are powerfully influenced by weightings (1–8) assigned to each domain.
Kevin Zhang +8 more
wiley +1 more source