Double LA-transform and their properties for solving partial differential equations

Hussein, Noor A.; Helal, May Mohammed; Tawfiq, L. N. M.

doi:10.1063/5.0163295

2nd International Conference of Mathematics, Applied Sciences, Information and Communication Technology

2023

DOI: 10.1063/5.0163295

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Double LA-transform and their properties for solving partial differential equations

Noor A. Hussein,

May Mohammed Helal,

L. N. M. Tawfiq

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2024

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Design optimal neural network based on new LM training algorithm for solving 3D - PDEs

Ghazi,

Tawfiq

2024

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Design optimal neural network based on new LM training algorithm for solving 3D - PDEs

Ghazi,

Tawfiq

2024

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

View full text Add to dashboard Cite

show abstract

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Double LA-transform and their properties for solving partial differential equations

Cited by 1 publication

References 23 publications

Design optimal neural network based on new LM training algorithm for solving 3D - PDEs

Design optimal neural network based on new LM training algorithm for solving 3D - PDEs

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