Results 51 to 60 of about 200,311 (278)
Next MaterialsThis work deals with the machine learning techniques used to build predictive models to determine the phases in complex concentrated alloys (CCAs). Two different approaches were employed to determine the presence of phases.
Kaven A.S. +2 more
doaj +1 more source
Stroke Prediction with Enhanced Gradient Boosting Classifier and Strategic Hyperparameter [PDF]
A stroke is a medical condition that occurs when the blood supply to the brain is interrupted. Stroke can cause damage to the brain that can potentially affect a person’s function and ability to move, speak, think, and feel normally. The effect of stroke
Aditya, Christian Sri Kusuma +3 more
core +2 more sources
Arthritis Care &Research, EarlyView.Objective We developed a novel electronic health record sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk +16 more
wiley +1 more source
Machine learning regression models for internal shame
Acta PsychologicaThis study aims to predict Internal Shame (IS) based on childhood trauma, social emotional competence, cognitive flexibility, distress tolerance and alexithymia in an Iranian sample.
Nataša Kovač +3 more
doaj +1 more source
Big Data and Cognitive Computing, 2022 Gradient boosting ensembles have been used in the cyber-security area for many years; nonetheless, their efficacy and accuracy for intrusion detection systems (IDSs) remain questionable, particularly when dealing with problems involving imbalanced data ...
Maya Hilda Lestari Louk, Bayu Adhi Tama
doaj +1 more source
Generalized Boosting Algorithms for Convex Optimization [PDF]
, 2011 Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks, we analyze gradient-based descent algorithms for boosting with respect to ...
Bagnell, J. Andrew, Grubb, Alexander
core +1 more source
A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller
International Journal of Adaptive Control and Signal Processing, EarlyView.Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg +5 more
wiley +1 more source
Ensemble machine learning models for ternary electrolyte viscosity prediction
Chemical Thermodynamics and Thermal AnalysisAccurate viscosity prediction in ternary electrolyte systems is essential for oil and gas drilling, geothermal operations, and brine processing. This comprehensive study compared three boosting-based ensemble machine learning algorithms - Gradient ...
Vinita Sangwan +3 more
doaj +1 more source
Totally Corrective Multiclass Boosting with Binary Weak Learners [PDF]
, 2010 In this work, we propose a new optimization framework for multiclass boosting learning. In the literature, AdaBoost.MO and AdaBoost.ECC are the two successful multiclass boosting algorithms, which can use binary weak learners.
Barnes, Nick +3 more
core
Advanced Engineering Materials, EarlyView.Thermomechanical fatigue tests of laser beam powder bed fusion (PBF‐LB) Inconel 718 show that the additively manufactured material reaches almost the lifetimes of conventionally‐rolled material under no‐dwell conditions. Introducing dwell times at the maximum temperature markedly reduces the lifetimes due to pronounced grain boundary sliding associated
Stefan Guth +6 more
wiley +1 more source