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Numerical simulation of natural convection in a differentially heated cubical cavity with solid fins

International Journal of Numerical Methods for Heat & Fluid Flow
Purpose The performance of solid fins inside a differentially heated cubical cavity is numerically studied in this paper. The main purpose of the study is to make an optimization to reach the maximum heat transfer in the enclosure having the solid fins ...
Xuan Hoang Khoa Le   +2 more
semanticscholar   +1 more source

Euclid preparation: LXVII. Deep learning true galaxy morphologies for weak lensing shear bias calibration

Astronomy & Astrophysics
To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified ...
Euclid Collaboration B. Csizi   +499 more
semanticscholar   +1 more source

Improved Learning Algorithms of SLFN for Approximating Periodic Function

2008
In this paper, three improved Extreme Learning Machines (ELMs) are proposed to approximating periodic function. According to Fourier series expansion theory, the hidden neurons activation functions in the improved ELM are a class of sine and cosine functions.
openaire   +1 more source

A growing and pruning sequential learning algorithm of hyper basis function neural network for function approximation

Neural Networks, 2013
Radial basis function (RBF) neural network is constructed of certain number of RBF neurons, and these networks are among the most used neural networks for modeling of various nonlinear problems in engineering. Conventional RBF neuron is usually based on Gaussian type of activation function with single width for each activation function.
Vuković, Najdan, Miljković, Zoran
openaire   +3 more sources

A novel iterative algorithm for approximating equivalent circuits of numerical transfer functions

International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 2016
AbstractRecently, we presented a novel method for pole residue equivalent system solver (PRESS). In this work, we provide the exact solution of local fit types 1, 2, and 3. We also modify the original algorithm to conduct parallel search for optimal solution across all frequencies, instead of targeting only the peak error.
Ata Zadehgol, Venkatesh Avula
openaire   +1 more source

An Adaptive Algorithm for Weighted Approximation of Singular Functions over $\mathbb{R}$

SIAM Journal on Numerical Analysis, 2013
We study the $\omega$-weighted $L^p$ approximation ($1\le p\le\infty$) of piecewise $r$-smooth functions $f:\mathbb{R}\to\mathbb{R}$. Approximations $\mathcal{A}_nf$ are based on $n$ values of $f$ at points that can be chosen adaptively. Assuming that the weight $\omega$ is Riemann integrable on any compact interval and asymptotically decreasing, a ...
Leszek Plaskota   +2 more
openaire   +1 more source

Numerical solutions for optimal control of stochastic Kolmogorov systems with regime-switching and random jumps

Statistical Inference for Stochastic Processes : An International Journal devoted to Time Series Analysis and the Statistics of Continuous Time Processes and Dynamical Systems, 2022
Hongjiang Qian, Zhexin Wen, G. Yin
semanticscholar   +1 more source

Euclid preparation. LV. Exploring the properties of proto-clusters in the Simulated Euclid Wide Survey

Astronomy & Astrophysics
Galaxy proto-clusters are receiving increased interest since most of the processes shaping the structure of clusters of galaxies and their galaxy population happen at the early stages of their formation.
Euclid Collaboration H. Bohringer   +499 more
semanticscholar   +1 more source

Statistical Modeling

A Methodology to Model the Statistical Fracture Behavior of Acrylic Glasses for Stochastic Simulation, 2021
Marcel Berlinger
semanticscholar   +1 more source

The convergence rate of the sandwich algorithm for approximating convex functions

Computing, 1992
Interval bisection, slope bisection, maximum error rule and chord rule are considered as four natural rules leading to different versions of the sandwich algorithm for approximating a convex function of one variable over an interval by evaluating the function and its derivative at a sequence of points.
openaire   +1 more source

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