
In this study, a new approach to basis of intelligent systems and machine learning algorithms is introduced for solving singular multi-pantograph differential equations (SMDEs). For the first time, a type-2 fuzzy logic based approach is formulated to find an approximated solution. The rules of the suggested type-2 fuzzy logic system (T2-FLS) are optimized by the square root cubature Kalman filter (SCKF) such that the proposed fineness function to be minimized. Furthermore, the stability and boundedness of the estimation error is proved by novel approach on basis of Lyapunov theorem. The accuracy and robustness of the suggested algorithm is verified by several statistical examinations. It is shown that the suggested method results in an accurate solution with rapid convergence and a lower computational cost.
ddc:510, Lyapunov function, square root cubature kalman filter, Science, Physics, QC1-999, Q, Fuzzy-Regelung, singular multi-pantograph differential equations, Astrophysics, Article, 510, QB460-466, square root cubature calman filter, statistical analysis, bk:31.78, fuzzy systems, 518, OA-Publikationsfonds2020
ddc:510, Lyapunov function, square root cubature kalman filter, Science, Physics, QC1-999, Q, Fuzzy-Regelung, singular multi-pantograph differential equations, Astrophysics, Article, 510, QB460-466, square root cubature calman filter, statistical analysis, bk:31.78, fuzzy systems, 518, OA-Publikationsfonds2020
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