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A novel technique to study the solutions of time fractional nonlinear smoking epidemic model
A novel technique to study the solutions of time fractional nonlinear smoking epidemic model
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A novel technique to study the solutions of time fractional nonlinear smoking epidemic model
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A novel technique to study the solutions of time fractional nonlinear smoking epidemic model
A novel technique to study the solutions of time fractional nonlinear smoking epidemic model

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A novel technique to study the solutions of time fractional nonlinear smoking epidemic model
A novel technique to study the solutions of time fractional nonlinear smoking epidemic model
Journal Article

A novel technique to study the solutions of time fractional nonlinear smoking epidemic model

2024
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Overview
The primary goal of the current work is to use a novel technique known as the natural transform decomposition method to approximate an analytical solution for the fractional smoking epidemic model. In the proposed method, fractional derivatives are considered in the Caputo, Caputo–Fabrizio, and Atangana–Baleanu–Caputo senses. An epidemic model is proposed to explain the dynamics of drug use among adults. Smoking is a serious issue everywhere in the world. Notwithstanding the overwhelming evidence against smoking, it is nonetheless a harmful habit that is widespread and accepted in society. The considered nonlinear mathematical model has been successfully used to explain how smoking has changed among people and its effects on public health in a community. The two states of being endemic and disease-free, which are when the disease dies out or persists in a population, have been compared using sensitivity analysis. The proposed technique has been used to solve the model, which consists of five compartmental agents representing various smokers identified, such as potential smokers V , occasional smokers G , smokers T , temporarily quitters O , and permanently quitters W . The results of the suggested method are contrasted with those of existing numerical methods. Finally, some numerical findings that illustrate the tables and figures are shown. The outcomes show that the proposed method is efficient and effective.