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dc.contributor.authorDong, Jun
dc.date.accessioned2024-12-24T18:48:11Z
dc.date.available2024-12-24T18:48:11Z
dc.date.copyright8/22/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn1555-1415
dc.identifier.othercnd_019_10_101005.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4302770
dc.description.abstractThe traditional linear generation fuzzy fractional differential equation parameter identification algorithm lacks the update of the parameter identification process, has a large amount of calculation, slow convergence speed of parameter identification, and strong dependence on initial values. In this paper, a new intelligent recognition algorithm for linearly generated fuzzy fractional differential equations is proposed. The parameters of the equation are re-expressed by the constant level set. The piecewise constant level set algorithm based on equation parameter intelligent identification is used to solve the steady-state solution of fractional differential equation, and the nonconvergence problem caused by too much calculation is solved. A new algorithm scheme for linearly generating fuzzy fractional differential equations is established, the constraints of the level set of the differential equations are calculated, and the updated algorithm for parameter identification of the equation is obtained. The evolutionary algorithm is used to solve the updating algorithm to realize the intelligent identification algorithm of linear fractional fuzzy differential equations. Experimental results showed that the algorithm had the advantages of fast convergence speed, high calculation accuracy, and low initial value.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleAn Intelligent Parameter Identification Algorithm of Linear Fuzzy Fractional Differential Equation
dc.typeJournal Paper
dc.journal.volume19
dc.journal.issue10
dc.journal.titleJournal of Computational and Nonlinear Dynamics
dc.identifier.doi10.1115/1.4066093
dc.journal.fristpage101005-1
dc.journal.lastpage101005-6
dc.page6
dc.treeJournal of Computational and Nonlinear Dynamics:;2024:;volume( 019 ):;issue: 010
dc.contenttypeFulltext


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