Akram, MuhammadMuhammad, GhulamAllahviranloo, TofighPedrycz, Witold2024-05-192024-05-1920230165-01141872-6801https://doi.org10.1016/j.fss.2023.108725https://hdl.handle.net/20.500.12713/5150This article aims to introduce and investigate the analytical fuzzy solution of the incommensurate non-homogeneous system of fuzzy linear fractional differential equations (INS-FLFDEs) using trivariate Mittag-Leffler functions. Entries of the coefficient matrix of the given system are treated as real numbers, initial-values are triangular fuzzy numbers (TFNs), and the forcing function is a fuzzy set (or a bunch) of real function. We extract the potential solution in the form of a fuzzy bunch of real functions (FBoRFs) rather than the solution of fuzzy-valued functions. We formulate the fuzzy initial value problem as a set of classical initial value problems by taking the forcing function from the class of FBoRFs and the initial value from the collection of TFNs (as a special case). The solution of this system is in the form of a trivariate Mittag-Leffler function. We interpret this solution as an element of the fuzzy solution set and assign the minimum value of membership that takes from the forcing function and the initial value in the fuzzy set. The originality of the proposed technique is that the uncertainty is smaller compared to the uncertainty extracted from other techniques. In addition, generalized derivatives increase the order and dimension of the system. Therefore, the proposed technique is better in terms of complexity because it reduces the order and dimension of the system. Finally, to grasp the proposed technique, we solve the electrical network and multiple mass-spring systems as applications and analyze their graphs to visualize and support theoretical results.eninfo:eu-repo/semantics/closedAccessFuzzy Linear Fractional Differential EquationsCaputo Fractional DerivativeFuzzy Bunch Of Real FunctionsTrivariate Mittag-Leffler FunctionIncommensurate non-homogeneous system of fuzzy linear fractional differential equations using the fuzzy bunch of real functionsArticle473WOS:0010969505000012-s2.0-85173575324N/A10.1016/j.fss.2023.108725Q1