Results 141 to 150 of about 3,817,143 (297)
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, EarlyView.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Residual based selection of smoothing parameters
, 2004 Die vorliegende Dissertation beschäftigt sich mit der speziellen Problematik der Glättungsparameter-Wahl in der Nichtparametrischen Regression. Da Standardverfahren wie z.B. Kernschätzer, lokale Polynom-Anpassungen und Splines jeweils mindestens einen Glättungsparameter benötigen, stellt sich die Frage, wie diese automatisch auch für komplizierte ...
openaire +2 more sources
Advanced Engineering Materials, EarlyView.PUF/ENB microcapsules were synthesized based on a sequential factorial design and incorporated into an epoxy matrix. Their anticorrosive action, associated with the self‐healing mechanism, demonstrated that the addition of microcapsules to the coating improved anticorrosive performance compared to pure epoxy coatings, particularly when the encapsulate ...
Vandicleya Alves Moreira +6 more
wiley +1 more source
Heterogeneous Information and Appraisal Smoothing [PDF]
This study examines the heterogeneous appraiser behavior and its implication on the traditional appraisal smoothing theory. We show that the partial adjustment model is consistent with the traditional appraisal smoothing argument only when all the ...
Yingchun Liu, Zhenguo Lin, Ping Cheng
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Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Advanced Engineering Materials, EarlyView.Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Robust smoothing: Smoothing parameter selection and applications to fluorescence spectroscopy
Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise.
Lee, Jong Soo, Cox, Dennis D.
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Local Linear Forecasts Using Cubic Smoothing Splines [PDF]
We show how cubic smoothing splines fitted to univariate time series data can be used to obtain local linear forecasts. Our approach is based on a stochastic state space model which allows the use of a likelihood approach for estimating the smoothing ...
Baki Billah +3 more
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Advanced Engineering Materials, EarlyView.Additively manufactured AlCrFe2Ni2 with contrasting BCC/B2‐dominant and lamellar FCC + BCC/B2 microstructures exhibits the same pressure‐induced BCC/B2 → HCP transformation. Under laser heating at high pressure, HCP is destabilized, and a cubic BCC/B2 + FCC assemblage is recovered, while the lower‐scan‐speed microstructure transforms at a lower ...
Raimundas Sereika +5 more
wiley +1 more source
Data-driven smoothing parameter selection in density estimation
, 2021 Kernel density estimation (KDE) is a seasoned concept in nonparametric density estimation problems. KDE accuracy depends on the shape of the kernel as well as the bandwidth of the kernel. However, the shape of the kernel has only a minor influence on the estimation, whereas selecting proper smoothing parameter (bandwidth) is critical.
openaire +1 more source
An Improved Method for Bandwidth Selection when Estimating ROC Curves [PDF]
The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups.
Peter Hall, Rob J. Hyndman
core