Results 101 to 110 of about 24,811,169 (263)

Elastoplasticity Informed Kolmogorov–Arnold Networks Using Chebyshev Polynomials

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Multilayer perceptron (MLP) networks are predominantly used to develop data‐driven constitutive models for granular materials. They offer a compelling alternative to traditional physics‐based constitutive models in predicting non‐linear responses of these materials, for example, elastoplasticity, under various loading conditions. To attain the
Farinaz Mostajeran, Salah A. Faroughi
wiley   +1 more source

Analysis of IVPs and BVPs on Semi-Infinite Domains via Collocation Methods

Journal of Applied Mathematics, 2012
We study the numerical solutions to semi-infinite-domain two-point boundary value problems and initial value problems. A smooth, strictly monotonic transformation is used to map the semi-infinite domain 𝑥∈[0,∞) onto a half-open interval 𝑡∈[−1,1).
Mohammad Maleki, Ishak Hashim, Saeid Abbasbandy   +2 more
doaj   +1 more source

Chebyshev solution of large linear systems

Journal of Computer and System Sciences, 1967
AbstractThe general problem considered is that of solving a linear system of equations which is singular or almost singular. A method is described which obtains a “solution” to the system which is stable with respect to small changes in the matrix elements.
openaire   +2 more sources

Pickin' up good vibrations: a systematic review of footfall detection and analysis in the realm of wildlife surveying

Wildlife Biology, EarlyView.
Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge, Luigi La Spada, Robert A. Briers, Niamh M. McHugh, Patrick J. C. White   +4 more
wiley   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Chebyshev Finite Difference Method for Solving Constrained Quadratic Optimal Control Problems

Journal of Mathematical Extension, 2011
. In this paper the Chebyshev finite difference method is employed for finding the approximate solution of time varying constrained optimal control problems.
M. Maleki*, M. Dadkhah Tirani
doaj  

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

Derivative-Extended Time Domain Reduction for Coupled Systems Using Chebyshev Expansion

Discrete Dynamics in Nature and Society, 2017
The time domain model reduction based on general orthogonal polynomials has been presented for linear systems. In this paper, we extend this approach by taking the derivative information of the system into account in the context of model reduction of ...
Xiaolong Wang, Yaolin Jiang, Jun Liu
doaj   +1 more source

A numerical approach for multi-dimensional ψ-Hilfer fractional nonlinear Galilei invariant advection–diffusion equations

Results in Physics
In this paper, we introduce the ψ-Hilfer fractional version of nonlinear Galilei-invariant advection–diffusion equations in one and two dimensions. A new type of basic functions, namely the ψ-Chebyshev cardinal functions (CFs), is introduced to establish
M.H. Heydari, M. Razzaghi, M. Bayram
doaj   +1 more source

Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies

International Economic Review, EarlyView.
ABSTRACT Proof‐of‐Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity <$<$1 for stability, while ASERT remains stable for any elasticity and ...
Kohei Kawaguchi, Junpei Komiyama, Shunya Noda   +2 more
wiley   +1 more source