Neural networking study of worms in a wireless sensor model in the sense of fractal fractional-Reference-Cited by-同舟云学术

Neural networking study of worms in a wireless sensor model in the sense of fractal fractional

Published:2023 Issue:11 Volume:8 Page:26406-26424
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Khan Aziz¹,Abdeljawad Thabet¹²³⁴,Alqudah Manar A.⁵

Affiliation:

1. Department of Mathematics and Sciences, Prince Sultan University, P.O. Box 66833, 11586 Riyadh, Saudi Arabia

2. Department of Medical Research, China Medical University, Taichung 40402, Taiwan

3. Department of Mathematics, Kyung Hee University 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea

4. Department of Mathematics and Applied Mathematics, Sefako Makgatho Health Sciences University, Garankuwa, Medusa 0204, South Africa

5. Department of Mathematical Sciences, Faculty of Science, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh 11671, Saudi Arabia

Abstract

<abstract><p>We are concerned with the analysis of the neural networks of worms in wireless sensor networks (WSN). The concerned process is considered in the form of a mathematical system in the context of fractal fractional differential operators. In addition, the Banach contraction technique is utilized to achieve the existence and unique outcomes of the given model. Further, the stability of the proposed model is analyzed through functional analysis and the Ulam-Hyers (UH) stability technique. In the last, a numerical scheme is established to check the dynamical behavior of the fractional fractal order WSN model.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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