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Artificial Neural Networks for the Wavelet Analysis of Lane-Emden Equations: Exploration of Astrophysical Enigma

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Date

2024

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis inc

Open Access Color

Green Open Access

No

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No
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Average
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Average
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Top 10%

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Abstract

The equations of Lane-Emden (LE) can be visualized in various phenomena of astrophysics, fluid mechanics, polymer science and material science, thus the main concern of the present study is to put a novel effort to resolve these equations by utilizing the artificial neural networking approach incorporation with Vieta-Lucas wavelets called as VLW-ANN method. This unique combination of neural networking and Vieta-Lucas wavelets has been prepared to reduce the computational challenges as well as to overcome the obstacles while dealing with singularity. Many examples of the LE variety are solved by this approach. The effectiveness, accuracy and simplicity of the VLW-ANN scheme are demonstrated by a comparative study between the VLW-ANN results and existing results. Additionally, the results are shown in tables and figures, which give a more favorable impression of the scheme's dependability. VLW-ANN scheme will provide interesting results for other non-linear models.

Description

Keywords

Vieta-Lucas Wavelet, Lane-Emden Equation, Artificial Neural Network

Fields of Science

Citation

Kumar, Rakesh; Aeri, Shivani; Baleanu, Dumitru (2024). "Artificial neural networks for the wavelet analysis of Lane-Emden equations: exploration of astrophysical enigma", International Journal of Modelling and Simulation.

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OpenCitations Citation Count
3

Source

International Journal of Modelling and Simulation

Volume

45

Issue

Start Page

1711

End Page

1722
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CrossRef : 3

Scopus : 3

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Mendeley Readers : 3

SCOPUS™ Citations

3

checked on Feb 24, 2026

Web of Science™ Citations

7

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4

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7.03947739

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