Results 61 to 70 of about 4,577,308 (305)
Evaluation of Survival Analysis Models for Predicting Factors Infuencing the Time of Brucellosis Diagnosis [PDF]
Journal of Kerman University of Medical Sciences, 2019 Background:Brucellosis or Malta fever is one of the most common zoonotic diseases in the world. In addition to causing human suffering and dire economic impact on animals, due to the high prevalence of Brucellosis in the western regions of Isfahan ...
Sadegh kargarian-Marvasti +2 more
doaj +1 more source
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
SDA: a semi-parametric differential abundance analysis method for metabolomics and proteomics data
BMC Bioinformatics, 2019 Background Identifying differentially abundant features between different experimental groups is a common goal for many metabolomics and proteomics studies.
Yuntong Li +7 more
doaj +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +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 +17 more
wiley +1 more source
Semi-parametric Models for Satisfaction with Income [PDF]
An overview is presented of some parametric and semi-parametric models, estimators, and specification tests that can be used to analyze ordered response variables.In particular, limited dependent variable models that generalize or-dered probit are ...
Bellemare, C. +2 more
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Optimization of the Production of Rubber Compounds Using Mathematical Models
Advanced Engineering Materials, EarlyView.Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle +7 more
wiley +1 more source
Predictive Densities for Day-Ahead Electricity Prices Using Time-Adaptive Quantile Regression
Energies, 2014 A large part of the decision-making problems actors of the power system are facing on a daily basis requires scenarios for day-ahead electricity market prices.
Tryggvi Jónsson +3 more
doaj +1 more source
Semi-Parametric Hedonic Models, and Empirical Comparison [PDF]
Hedonic models have been widely used in the literature for valuation of non- market goods such as air quality. While the inclusion of air quality variables in hedonic models is common in applied work, there is not theoretical basis for defining the ...
Nancy Lozano-Gracia
core
Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source