Multi-objective T-S fuzzy control of Covid-19 spread model: An LMI approach.

Reza Najarzadeh, Mohammad Hassan Asemani, Maryam Dehghani, Mokhtar Shasadeghi

Abstract read

In one paragraph

Article in Biomedical signal processing and control, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates.Computer methods and programs in biomedicine · 2023
Article

4 · The record

Corrections and comments

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

4 authors.

Reza NajarzadehSchool of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.

Mohammad Hassan AsemaniSchool of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.

Maryam DehghaniSchool of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.

Mokhtar ShasadeghiDepartment of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the importance of control actions in spreading coronavirus disease, this paper is devoted to first modeling and then proposing an appropriate controller for this model. In the modeling procedure, we used a nonlinear mathematical model for the covid-19 outbreak to form a T-S fuzzy model. Then, for proposing the suitable controller, multiple optimization techniques including Linear Quadratic Regulator (LQR) and mixed

Indexed as

Covid 19 modelLinear matrix inequalities (LMIs)Multi objective controllerRobust T-S fuzzy controller

Identifiers

PMID35996470

DOI10.1016/j.bspc.2022.104107

PMCPMC9385779

What OpenQuestion holds

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Registered trials

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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.