A Numerical Study of the Dynamics of Vector-Born Viral Plant Disorders Using a Hybrid Artificial Neural Network Approach.

Hosam Alhakami, Muhammad Umar, Muhammad Sulaiman, Wajdi Alhakami, Abdullah Baz

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Mathematical Modeling in Systems Biology.Entropy (Basel, Switzerland) · 2023
Article

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hosam AlhakamiDepartment of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia.ORCID 0000-0002-4908-5573

Muhammad UmarDepartment of Mathematics, Abdul Wali Khan University, Mardan 23200, Pakistan.ORCID 0000-0002-6534-2920

Muhammad SulaimanDepartment of Mathematics, Abdul Wali Khan University, Mardan 23200, Pakistan.ORCID 0000-0002-4040-6211

Wajdi AlhakamiDepartment of Information Technology, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia.ORCID 0000-0003-1230-9470

Abdullah BazDepartment of Computer Engineering, College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia.ORCID 0000-0002-8669-6883

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most plant viral infections are vector-borne. There is a latent period of disease inside the vector after obtaining the virus from the infected plant. Thus, after interacting with an infected vector, the plant demonstrates an incubation time before becoming diseased. This paper analyzes a mathematical model for persistent vector-borne viral plant disease dynamics. The backpropagated neural network based on the Levenberg-Marquardt algorithm (NN-BLMA) is used to study approximate solutions for fluctuations in natural plant mortality and vector mortality rates. A state-of-the-art numerical technique is utilized to generate reference data for obtaining surrogate solutions for multiple cases through NN-BLMA. Curve fitting, regression analysis, error histograms, and convergence analysis are used to assess accuracy of the calculated solutions. It is evident from our simulations that NN-BLMA is accurate and reliable.

Indexed as

artificial neural networksdelay differential equationsLevenberg—Marquardt algorithmmachine learningmathematical modelingnumerical solutionsoptimization techniques

Identifiers

PMID36359604

DOI10.3390/e24111511

PMCPMC9689980

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LicenceCC BY

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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.