Bio-Inspired Numerical Analysis of COVID-19 with Fuzzy Parameters

Allehiany, F.M.; Dayan, Fazal; Al-Harbi, F. F.; Althobaiti, Nesreen; Ahmed, Nauman; Rafiq, Muhammad; Raza, Ali; Elamin, Mawahib

doi:10.32604/cmc.2022.025811

Cited by 12 publications

(8 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The maximum symptom of COVID-19 is similar to that of pneumonia, so these CT scan images help us get a clear-cut idea of this. So if the disease is detected early with proper care and medication, it can be cured and prevented from further spread [32].…”

Section: Motivation For Workmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

Swamy¹,

Praveen²,

Ahmed³

et al. 2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

Coronavirus 2019 (COVID -19) is the current global buzzword, putting the world at risk. The pandemic's exponential expansion of infected COVID-19 patients has challenged the medical field's resources, which are already few. Even established nations would not be in a perfect position to manage this epidemic correctly, leaving emerging countries and countries that have not yet begun to grow to address the problem. These problems can be solved by using machine learning models in a realistic way, such as by using computer-aided images during medical examinations. These models help predict the effects of the disease outbreak and help detect the effects in the coming days. In this paper, Multi-Features Decease Analysis (MFDA) is used with different ensemble classifiers to diagnose the disease's impact with the help of Computed Tomography (CT) scan images. There are various features associated with chest CT images, which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from pneumonia. The current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better results. The model's performance is assessed using Receiver Operating Characteristic (ROC) curve, the Root Mean Square Error (RMSE), and the Confusion Matrix. It is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.

show abstract

Section: Motivation For Workmentioning

confidence: 99%

“…They are exact solutions to decision trees. Here the inclusion of an additional layer helps get increased values in predictions [32]. Standard deviations and regression are shown in Eqs.…”

Section: Description Of Classification Algorithms Usedmentioning

confidence: 99%

Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

Swamy¹,

Praveen²,

Ahmed³

et al. 2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

show abstract

“…NSFD theory introduced by Mickens [27] is extensively used in the mathematical and numerical modeling of diseases. Allehiany et al studied the COVID-19 dynamics using NSFD in fuzzy senses [28]. Dayan et al developed an NSFD scheme to observe the spread of rumors and coronavirus dynamics [29,30].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Computer Virus Propagation with Fuzzy Parameters

Alhebshi¹,

Ahmed²,

Băleanu³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

Typically, a computer has infectivity as soon as it is infected. It is a reality that no antivirus programming can identify and eliminate all kinds of viruses, suggesting that infections would persevere on the Internet. To understand the dynamics of the virus propagation in a better way, a computer virus spread model with fuzzy parameters is presented in this work. It is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity, which depends on the quantity of virus. Considering this, the parameters β and γ being functions of the computer virus load, are considered fuzzy numbers. Using fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical models. The essential features of the model, like reproduction number and equilibrium analysis, are discussed in fuzzy senses. Moreover, with fuzziness, two numerical methods, the forward Euler technique, and a nonstandard finite difference (NSFD) scheme, respectively, are developed and analyzed. In the evidence of the numerical simulations, the proposed NSFD method preserves the main features of the dynamic system. It can be considered a reliable tool to predict such types of solutions.

show abstract

“…Many other researchers used various approaches using fuzzy theory to prevent strategies to combat deadly diseases [18][19][20][21][22]. Allehiany et al studied the SIR model in fuzzy senses and proposed different numerical and mathematical schemes to solve the model [23]. Mickens et al constructed a SEIQR model with fuzzy parameters and developed a fuzzy NSFD method, an extension of the Mickens NSFD theory [24], to solve the studied model [25].…”

Section: Introductionmentioning

confidence: 99%

Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

Dayan¹,

Băleanu²,

Ahmed³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

The application of fuzzy theory is vital in all scientific disciplines. The construction of mathematical models with fuzziness is little studied in the literature. With this in mind and for a better understanding of the disease, an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classical model of malaria transmission. The parameters β and δ, being function of the malaria virus load, are considered fuzzy numbers. Three steady states and the reproduction number of the model are analyzed in fuzzy senses. A numerical technique is developed in a fuzzy environment to solve the studied model, which retains essential properties such as positivity and dynamic consistency. Moreover, numerical simulations are carried out to illustrate the analytical results of the developed technique. Unlike most of the classical methods in the literature, the proposed approach converges unconditionally and can be considered a reliable tool for studying malaria disease dynamics.

show abstract

Bio-Inspired Numerical Analysis of COVID-19 with Fuzzy Parameters

Cited by 12 publications

References 42 publications

Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

Modeling of Computer Virus Propagation with Fuzzy Parameters

Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

Contact Info

Product

Resources

About