Fractional Dynamics and Recurrence Analysis in Cancer Model

Gabrick, Enrique C.; Sales, Matheus R.; Sayari, Elaheh; Trobia, José; Lenzi, Ervin K.; Borges, Fernando S.; Szezech, José D.; Iarosz, Kelly C.; Viana, Ricardo L.; Caldas, Iberê L.; Batista, Antonio M.

doi:10.1007/s13538-023-01359-w

Cited by 2 publications

(1 citation statement)

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“…The proposed method aggregates multi-level fisher vectors generated from completed local fractional order derivative feature vectors. Disease models [25] by various authors also help us gain meaningful insights into recent applications [26,27]. El-Mesady et al [28] presented a comprehensive analysis of the stability and control of the fractional-order monkeypox virus infection model, whereas Higazy et al [29].…”

Section: Fractional Order Applications In Multi-disciplinary Fieldsmentioning

confidence: 99%

Analyzing election trends incorporating memory effect through a fractional-order mathematical modeling

Santra,

Mahapatra

2024

Phys. Scr.

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This study proposes a new mathematical model to analyze and predict the results of a political election. In general, we predict or analyze the results using statistical methods; however, to minimize the effort of the study, we propose a fractional-order modeling approach. This study proposes a model to analyze and predict general election result trends in India, focusing on the state of West Bengal. To incorporate memory into the model, we consider the Caputo fractional derivative. The model solution's positivity, boundedness, existence, and uniqueness were tested analytically. Numerical simulations were carried out to investigate the impact of the parameters and evaluate the model's performance by incorporating the implications of the previous election for realistic situations. Following this, a qualitative analysis of the performance of political parties is discussed, and a prediction of the electoral victory is obtained.

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