Optimal Type-3 Fuzzy System for Solving Singular Multi-Pantograph Equations, By Ardashir Mohammadzadeh

Research

Title	Optimal Type-3 Fuzzy System for Solving Singular Multi-Pantograph Equations
Type	Article
Keywords	Machine learning artificial intelligence fuzzy systems Lyapunov stability learning algorithm multi-pantograph differential equations
Researchers	Chao Ma، Ardashir Mohammadzadeh، Hamza Turabieh، Majdi Mafarja، Shahab S، Amirhosein Mosavi

Abstract

In this study a new machine learning technique is presented to solve singular multi-pantograph differential equations (SMDEs). A new optimized type-3 fuzzy logic system (T3-FLS) by unscented Kalman filter (UKF) is proposed for solution estimation. The convergence and stability of presented algorithm are ensured by the suggested Lyapunov analysis. By two SMDEs the effectiveness and applicability of the suggested method is demonstrated. The statistical analysis show that the suggested method results in accurate and robust performance and the estimated solution is well converged to the exact solution. The proposed algorithm is simple and can be applied on various SMDEs with variable coefficients.