Results 61 to 70 of about 197,316 (278)
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
Proximal boosting and its acceleration
, 2020 Gradient boosting is a prediction method that iteratively combines weak learners to produce a complex and accurate model. From an optimization point of view, the learning procedure of gradient boosting mimics a gradient descent on a functional variable ...
Boyer, Claire +2 more
core
, 2015 We extend the theory of boosting for regression problems to the online learning setting. Generalizing from the batch setting for boosting, the notion of a weak learning algorithm is modeled as an online learning algorithm with linear loss functions that competes with a base class of regression functions, while a strong learning algorithm is an online ...
Beygelzimer, Alina +3 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.In this work, a magnetic core‐shell catalyst (HOF‐on‐Fe3O4/ZIF‐67) is successfully synthesized, consisting of a metal–organic framework (ZIF‐67) with magnetic Fe3O4 as the core and a porous hydrogen‐bonded organic framework (HOF) as the shell. The catalyst efficiently activated peroxymonosulfate, resulting in rapid and effective removal of water ...
Yingying Du +4 more
wiley +1 more source
Machine Learning Approaches for Fatigue Life Prediction of Steel and Feature Importance Analyses
InfrastructuresPredicting fatigue behavior in steel components is highly challenging due to the nonlinear and uncertain nature of material degradation under cyclic loading.
Babak Naeim +6 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar +8 more
wiley +1 more source
Frontiers in Public Health, 2022 BackgroundIn this paper, we examine whether machine learning and deep learning can be used to predict difficult airway intubation in patients undergoing thyroid surgery.MethodsWe used 10 machine learning and deep learning algorithms to establish a ...
Cheng-Mao Zhou +7 more
doaj +1 more source
Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization
, 2017 We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of parameter optimization using Bayesian optimization (Tree Parzen Estimator,
Kojima, Ryosuke +6 more
core +2 more sources
Advanced Functional Materials, EarlyView.This work discusses the use of blended channel materials in OECTs. It explores how mixing glycolated and alkoxylated polymers in various ratios offers a simpler and more efficient route to tuning OECT properties. The performance of the polymer blends is compared to the corresponding copolymers, demonstrating similar OECT characteristics, swelling ...
Lize Bynens +14 more
wiley +1 more source
An Evaluation of Classification and Outlier Detection Algorithms [PDF]
, 2018 This paper evaluates algorithms for classification and outlier detection accuracies in temporal data. We focus on algorithms that train and classify rapidly and can be used for systems that need to incorporate new data regularly.
Austin, Jim, Hodge, Victoria J.
core +1 more source