Results 81 to 90 of about 3,187,155 (299)
Advanced Science, EarlyView.Machine learning‐guided strain engineering enables highly active, durable, support‐free Pt–Ni nanonetwork catalysts for the oxygen reduction reaction. Analysis of a Pt‐based catalyst dataset identifies surface compressive strain as an effective descriptor associated with enhanced activity and provided practical design guidelines.
Aparna Chitra Sudheer +4 more
wiley +1 more source
Using Ridge Regression & Generalized Maximum Entropy for the Aanalysis of the Environmental Pollution of Kirkuk Cement Factory [PDF]
المجلة العراقية للعلوم الاحصائية, 2010 This paper specifies econometric model for environmental pollution such as solid waste and gas emissions of Kirkuk cement factory for the period (1984-2006) the variables used in the production process, which is electric power, black oil, clay and ...
doaj +1 more source
The Distribution of Stochastic Shrinkage Parameters in Ridge Regression [PDF]
In this article we derive the density and distribution functions of the stochastic shrinkage parameters of three well-known operational Ridge Regression estimators by assuming normality. The stochastic behavior of these parameters is likely to affect the
Luis Firinguetti, Hernán Rubio
core
Generalized structured additive regression based on Bayesian P-splines [PDF]
, 2003 Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Bayesian GAM's and extensions to generalized structured additive regression ...
Lang, S., Brezger, Andreas, Lang, Stefan
core +1 more source
Advanced Science, EarlyView.Pasta is a transcriptomic aging clock built on an age‐shift learning framework and trained on 17 000 samples across 21 datasets. It accurately predicts relative biological age across tissues, platforms, and species, captures stemness‐to‐senescence transitions, and identifies age‐modulatory perturbations.
Jérôme Salignon +6 more
wiley +1 more source
A computer intensive method for choosing the ridge parameter [PDF]
In this paper we describe a computer intensive method to find the ridge parameter in a prediction oriented linear model. With the help of a factorial experimental design the method is tested and compared to a classical one.
Weihs, Claus +2 more
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Mesoporous‐Shell Monolayer Plasmonic Architecture Enables Quantitative and Decision‐Guided SERS
Advanced Science, EarlyView.Mesoporous‐shell‐regulated molecular transport combined with monolayer hotspot determinism transforms surface‐enhanced Raman spectroscopy (SERS) from ultrasensitive detection into quantitative and decision‐guided molecular sensing. ABSTRACT Quantitative surface‐enhanced Raman spectroscopy (SERS) has long been impeded by stochastic hotspot formation ...
Guangyao Huang +9 more
wiley +1 more source
The study presented Mult-, and Inverse-ridge regressions for data with or without multicollinearity for certain shrinkage factors. The study considered data of GDP of Nigeria as response, while exchange, unemployment, inflation and foreign direct investment were used as the predictors.
Ebikeme, Tari Emmanuel +2 more
openaire +2 more sources
Application of a Modified Generalized Regression Neural Networks Algorithm in Economics and Finance [PDF]
, 2011 In this paper we propose an alternative and modified Generalized Regression Neural Networks Autoregressive model (GRNN-AR) in S&P 500 and FTSE 100 index returns, as also in Gross domestic product growth rate of Italy, USA and UK. We compare the forecasts
Giovanis, Eleftherios
core
Advanced Science, EarlyView.Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu +8 more
wiley +1 more source