Results 131 to 140 of about 26,590 (142)
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International Journal of Biomathematics, 2019
Approximate analytical solution of the system of coupled nonlinear Ordinary Differential Equations (ODEs) of a biochemical reaction model is much relevant due to its practical significance to biochemists.
V. Dubey, Rajnesh Kumar, Devendra Kumar
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Approximate analytical solution of the system of coupled nonlinear Ordinary Differential Equations (ODEs) of a biochemical reaction model is much relevant due to its practical significance to biochemists.
V. Dubey, Rajnesh Kumar, Devendra Kumar
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Bayesian sampling using interacting particles
arXiv.orgBayesian sampling is an important task in statistics and machine learning. Over the past decade, many ensemble-type sampling methods have been proposed.
Shi Chen, Zhiyan Ding, Qin Li
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High-order expansion of Neural Ordinary Differential Equations flows
arXiv.orgArtificial neural networks, widely recognised for their role in machine learning, are now transforming the study of ordinary differential equations (ODEs), bridging data-driven modelling with classical dynamical systems and enabling the development of ...
Dario Izzo +3 more
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UMYU Scientifica
Study’s Excerpt:• The study evaluates numerical methods for ODEs to guide suitable model simulations.• Adomian Decomposition suits decay/growth models; block method excels in all problems, including SIR.• The study highlights numerical methods' ease and ...
Adamu Samuel +4 more
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Study’s Excerpt:• The study evaluates numerical methods for ODEs to guide suitable model simulations.• Adomian Decomposition suits decay/growth models; block method excels in all problems, including SIR.• The study highlights numerical methods' ease and ...
Adamu Samuel +4 more
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A meshfree approach for analysis and computational modeling of non-linear Schrödinger equation
Computational and Applied Mathematics, 2020Ram Jiwari +3 more
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SIAM Journal on Scientific Computing
Within the family of explainable machine-learning, we present Fredholm neural networks (Fredholm NNs), deep neural networks (DNNs) which replicate fixed point iterations for the solution of linear and nonlinear Fredholm Integral Equations (FIE) of the ...
Kyriakos Georgiou +2 more
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Within the family of explainable machine-learning, we present Fredholm neural networks (Fredholm NNs), deep neural networks (DNNs) which replicate fixed point iterations for the solution of linear and nonlinear Fredholm Integral Equations (FIE) of the ...
Kyriakos Georgiou +2 more
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International Journal of Convergent and Informatics Science Research
This study presents a comparative analysis of breast cancer tumor growth using two mathematical approaches: the classical first-order logistic ordinary differential equation (ODE) and a fractional ODE formulation.
AMADI UGWULO CHINYERE
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This study presents a comparative analysis of breast cancer tumor growth using two mathematical approaches: the classical first-order logistic ordinary differential equation (ODE) and a fractional ODE formulation.
AMADI UGWULO CHINYERE
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Applied Mathematics and Mechanics, 2020
A. Ahmed, M. Khan, J. Ahmed, A. Hafeez
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A. Ahmed, M. Khan, J. Ahmed, A. Hafeez
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Numerical methods in vehicle system dynamics: state of the art and current developments
, 2011Martin Arnold +4 more
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, 2006