Results 91 to 100 of about 4,452 (291)
Advanced Science, EarlyView.A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
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Modified Ridge Parameters for Seemingly Unrelated Regression Model [PDF]
In this paper, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity.
Shukur , Ghazi +2 more
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New ridge parameters for ridge regression [PDF]
, 2014 Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS) estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation.
Dorugade, A.V.
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Quality Thresholds for Angiogenesis Under Acoustic Manipulation in Engineered Vascular Tissues
Advanced Science, EarlyView.Defined biological and physical quality thresholds achieved through acoustic manipulation regulate cellular alignment and spatial organization, promoting self‐assembling vasculature, extracellular matrix deposition, and angiogenic responses, thereby establishing critical acoustic patterning requirements for engineered vascular tissue development in ...
Oscar O'Dwyer Lancaster‐Jones +5 more
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An efficient generalized ridge estimator for logistic regression model
Информатика. Экономика. УправлениеIn the logistic regression model (LRM), the maximum likelihood estimator (MLE) is commonly employed to estimate unknown model parameters. However, when substantial multicollinearity exists among the explanatory variables, the MLE produces unstable ...
Ахмед Мутлаг Алгбури
doaj +1 more source
Ridge regression estimators with the problem of multicollinearity
Applied Mathematical Sciences, 2013 Abstract The study aims to illustrate the negative effect of the Multicollinearity problem upon the specimen, identify the way of Ridge Regression as a way to deal with the Multicollinearity problem, focus on some of the estimators of Ridge regression as (James and Stein, Bhattacharya, Heuristic) and identify which estimator from the previously ...
Maie M. Kamel, Sarah F. Aboud
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Ridge regression revisited [PDF]
We argue in this paper that general ridge (GR) regression implies no major complication compared with simple ridge regression. We introduce a generalization of an explicit GR estimator derived by Hemmerle and by Teekens and de Boer and show that this ...
Hafner, C.M., Boer, P.M.C. de
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On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
Advanced Electronic Materials, EarlyView.ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
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The effect of high leverage points on the logistic ridge regression estimator having multicollinearity [PDF]
, 2013 This article is concerned with the performance of logistic ridge regression estimation technique in the presence of multicollinearity and high leverage points.
Ariffin @ Mat Zin, Syaiba Balqish +1 more
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Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations
Advanced Electronic Materials, EarlyView.This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka +5 more
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