Vol.73, No.2, 2022, pp.4441-4454, doi:10.32604/cmc.2022.029432
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ARTICLE
A Stochastic Study of the Fractional Order Model of Waste Plastic in Oceans
• Muneerah Al Nuwairan1,*, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Maryam Alnami1, Hanan Almuslem1
1 Department of Mathematics and Statistics, College of Science, King Faisal University, P. O. Box 400, Al-Ahsa, 31982, Saudi Arabia
2 Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan
3 Future Technology Research Center, National Yunlin University of Science and Technology, Douliou, Yunlin, 64002, Taiwan
* Corresponding Author: Muneerah Al Nuwairan. Email:
Received 03 March 2022; Accepted 23 May 2022; Issue published 16 June 2022
Abstract
In this paper, a fractional order model based on the management of waste plastic in the ocean (FO-MWPO) is numerically investigated. The mathematical form of the FO-MWPO model is categorized into three components, waste plastic, Marine debris, and recycling. The stochastic numerical solvers using the Levenberg-Marquardt backpropagation neural networks (LMQBP-NNs) have been applied to present the numerical solutions of the FO-MWPO system. The competency of the method is tested by taking three variants of the FO-MWPO model based on the fractional order derivatives. The data ratio is provided for training, testing and authorization is 77%, 12%, and 11% respectively. The exactness of LMQBP-NNs is observed by using the comparative performances of the obtained and the Adams-Bashforth-Moulton method. To verify the competence, validity, capability, exactness, and consistency of LMQBP-NNs, the performances have been obtained using the regression, state transitions, error histograms, correlation and mean square error.
Keywords
Fractional order; ocean; Adams-Bashforth-Moulton; Levenberg-Marquardt backpropagation; numerical solutions
Cite This Article
M. Al Nuwairan, Z. Sabir, M. Asif Zahoor Raja, M. Alnami and H. Almuslem, "A stochastic study of the fractional order model of waste plastic in oceans," Computers, Materials & Continua, vol. 73, no.2, pp. 4441–4454, 2022.
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