Yazar "Babakordi, Fatemeh" seçeneğine göre listele

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    A Cramer Method for Solving Fully Fuzzy Linear Systems Based on Transmission Average
    (Payame Noor University (PNU), 2022) Babakordi, Fatemeh; Allahviranloo, Tofigh
    Solving fuzzy linear systems has been widely studied during the last decades. However, there are still many challenges to solving fuzzy linear equations, as most of the studies have used the principle of extension, which suffers from shortcomings such as the lack of solution, achieving solutions under very strong conditions, large support of the obtained solutions, inaccurate or even incorrect solutions due to not utilizing all the available information, complicated process and high computational load. These problems motivated us to present a fuzzy Cramer method for solving fuzzy linear equations, which uses arithmetic operations based on the Transmission Average (TA). In this study, fully fuzzy linear systems in the form of à ˜X = ˜B, and dual fuzzy linear systems in the form of à ˜X + ˜B =˜C ˜X + ˜D are solved using the proposed fuzzy Cramer method, and numerical examples are provided to confirm the effectiveness and applicability of the proposed method. © 2022 by the authors.
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    Application of fuzzy ABC fractional differential equations in infectious diseases
    (Univ Tabriz, 2024) Babakordi, Fatemeh; Allahviranloo, Tofigh
    In this paper, for solving the HIV fuzzy mathematical model, it is first transformed into a system of three nonlinear fuzzy Atangana-Baleanu-Caputo (ABC) fractional differential equations with three unknowns and fuzzy initial values. Then, using the generalized Hukuhara difference and ABC fractional derivative and applying the fuzzy numerical ABC-PI method, its fuzzy solution is calculated. Moreover, some theorems are defined to prove the existence and uniqueness of the solution. Then, it is explained that the proposed method can be used for the system of any equations with unknowns.Therefore, in order to determine the solution of the fuzzy mathematical model of the transmission of COVID-19, it is transformed into a system of six nonlinear fuzzy Atangana-Baleanu-Caputo (ABC) fractional differential equations with six unknowns and fuzzy initial values and is solved similarly. At the end, a numerical example is presented to verify the effectiveness of the proposed method.
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    Fuzzy Laplace transform method for a fractional fuzzy economic model based on market equilibrium
    (Elsevier Science Inc, 2024) Babakordi, Fatemeh; Allahviranloo, Tofigh; Shahriari, M. R.; Catak, Muammer
    Fuzzy fractional models are of interest because they are very effective in describing real -world problems, but the analytical investigation of these models is often complex. Therefore, presenting a practical method for the analytical solution of these models is of particular importance. Hence, in this paper, first, the Laplace transform of the fuzzy ABC fractional derivative and its properties are introduced using the strongly generalized Hukuhara differentiability concept, and an analytical method for solving the fuzzy ABC fractional differential equation based on the Laplace transform is proposed. In the following, to show the comprehensiveness and appropriateness of the method, since the parameters are imprecise and ambiguous in economic problems, the price adjustment equation is modeled in the form of a fuzzy ABC fractional differential equation using the fuzzy ABC fractional derivative, and the fuzzy price for the adjustment equation is obtained using the proposed analytical fuzzy price. Finally, the effectiveness of the proposed approach is demonstrated with numerical examples.
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    Introducing and solving the hesitant fuzzy system A X = B
    (Systems Research Institute, Polish Academy of Sciences, 2022) Babakordi, Fatemeh; Allahviranloo, Tofigh
    In this paper the solution for hesitant fuzzy system as AX = B is introduced where A is an n ×n known hesitant fuzzy matrix, B is an n ×1 known hesitant fuzzy vector and X is an n ×1 unknown hesitant fuzzy vector. First, L?-norm and L1-norm of a hesitant fuzzy vector are intro-duced. Then, the concepts of hesitant fuzzy zero, ’almost equal’ and ’less than’ and ’equal’ are defined for two hesitant fuzzy numbers. Finally, using a minimization problem; the hesitant fuzzy system is solved. At the end, some numerical examples are presented to show the effectiveness of the proposed method
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    Soft modeling
    (Elsevier, 2024) Babakordi, Fatemeh; Taghi-Nezhad, Nemat Allah; Allahviranloo, Tofigh
    In this chapter of the book, we examine five practical and real-world models in the fuzzy environment. First, we discuss the fuzzy solution for the cancer tumor model under generalized Hukuhara-Caputo partial derivability using the fuzzy integral transformation. Then, the fuzzy classification system, which is used as a decision support tool for biologists in identifying dendritic cells, was investigated in the fuzzy environment. In the following, the quantitative model of economic production with decline under Marxist economics is expressed in the method of social political economy. The study of the model in a fuzzy environment is inevitable to fit the model to the real problem as much as possible. Another model that has been studied and is very efficient in the fuzzy environment is the market equilibrium value model. Finally, we explain the inventory model with the learning effect and the business credit strategy in the fuzzy environment for the buyer.