Results 61 to 70 of about 58,601 (260)

Simpson-visser-ads black holes: thermodynamics and binary merger

European Physical Journal C: Particles and Fields
In this article, we performed Simpson–Visser (SV)-regularization scheme to Anti-de Sitter (AdS) black holes and then studied thermal properties of the resulting spacetime geometry.
Neeraj Kumar, Ankur Srivastav, Phongpichit Channuie   +2 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Performance Analysis of Iterative Methods in Microwave Imaging With Various Regularization Techniques

IEEE Open Journal of Antennas and Propagation
Quantitative microwave imaging (MWI) involves solving the inverse scattering problem (ISP), which is characterized by nonlinearity and ill-posedness.
Reihaneh Ahmadi Vanhari, Ahmad Bakhtafrouz, Sima Noghanian   +2 more
doaj   +1 more source

Error estimates of a difference approximation method for a backward heat conduction problem

International Journal of Mathematics and Mathematical Sciences, 2006
We introduce a central difference method for a backward heat conduction problem (BHCP). Error estimates for this method are provided together with a selection rule for the regularization parameter (the space step length).
Xiang-Tuan Xiong, Chu-Li Fu, Zhi Qian, Xiang Gao   +3 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Bipartite regular graphs and shortness parameters

Discrete Mathematics, 1985
\textit{B. Grünbaum} and \textit{H. Walther} [J. Comb. Theory, Ser. A 14, 364-385 (1973; Zbl 0263.05103)] defined the shortness exponent \(\sigma\) (\({\mathcal G})\) and shortness coefficient \(\rho\) (\({\mathcal G})\) of an infinite class of graphs \({\mathcal G}\) as \(\sigma\) (\({\mathcal G})= \inf_{G\in {\mathcal G}}\frac{\log h(G)}{\log v(G)}\),
openaire   +2 more sources

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

A Mathematical Analysis of New L-curve to Estimate the Parameters of Regularization in TSVD Method

پژوهش‌های ریاضی, 2015
A new technique to find the optimization parameter in TSVD regularization method is based on a curve which is drawn against the residual norm [5]. Since the TSVD regularization is a method with discrete regularization parameter, then the above-mentioned ...
A.R. Keshvari, S.M Hosseni
doaj  

New Regularization Models for Image Denoising with a Spatially Dependent Regularization Parameter

Abstract and Applied Analysis, 2013
We consider simultaneously estimating the restored image and the spatially dependent regularization parameter which mutually benefit from each other. Based on this idea, we refresh two well-known image denoising models: the LLT model proposed by Lysaker ...
Tian-Hui Ma, Ting-Zhu Huang, Xi-Le Zhao
doaj   +1 more source