Evidence map›Paper›PMID 35140906›Full record

ArticleJournal of healthcare engineering

An Advance Computing Numerical Heuristic of Nonlinear SIR Dengue Fever System Using the Morlet Wavelet Kernel.

Muhammad Umar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, K S Al-Basyouni, S R Mahmoud, Yolanda Guerrero Sánchez

Abstract read
In one paragraph

Article in Journal of healthcare engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Muhammad UmarDepartment of Mathematics and Statistics, Hazara University, Mansehra, Pakistan.
Zulqurnain SabirDepartment of Mathematics and Statistics, Hazara University, Mansehra, Pakistan.
Muhammad Asif Zahoor RajaFuture Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan.
K S Al-BasyouniMathematics Department, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
S R MahmoudGRC Department, Faculty of Applied Studies, King Abdulaziz University, Jeddah, Saudi Arabia.
Yolanda Guerrero SánchezDepartment of Dermatology, Stomatology, Radiology and Physical Medicine, University of Murcia, Murcia, Spain.ORCID https://orcid.org/0000-0002-4228-2355

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study is associated to solve the nonlinear SIR dengue fever system using a computational methodology by operating the neural networks based on the designed Morlet wavelet (MWNNs), global scheme as genetic algorithm (GA), and rapid local search scheme as interior-point algorithm (IPA), i.e., GA-IPA. The optimization of fitness function based on MWNNs is performed for solving the nonlinear SIR dengue fever system. This MWNNs-based fitness function is accessible using the differential system and initial conditions of the nonlinear SIR dengue fever system. The designed procedures based on the MWNN-GA-IPA are applied to solve the nonlinear SIR dengue fever system to check the exactness, precision, constancy, and efficiency. The achieved numerical form of the nonlinear SIR dengue fever system via MWNN-GA-IPA was compared with the Runge-Kutta numerical results that verify the significance of MWNN-GA-IPA. Moreover, statistical reflections through different measures for the nonlinear SIR dengue fever system endorse the precision and convergence of the computational MWNN-GA-IPA.

Indexed as

DengueHeuristicsAlgorithmsExerciseHumansNeural Networks, Computer

Identifiers

PMID35140906
PMCPMC8820869

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.