Optimal Type-3 Fuzzy System for Solving Singular Multi-Pantograph Equations

作     者：Ma, Chao Mohammadzadeh, Ardashir Turabieh, Hamza Mafarja, Majdi Band, Shahab S. Mosavi, Amir 

作者机构：Shenzhen Inst Informat Technol Sch Digital Media Shenzhen 518172 Peoples R China Univ Bonab Dept Elect Engn Fac Engn Bonab *** Iran Taif Univ Dept Informat Technol Coll Comp & Informat Technol At Taif 21944 Saudi Arabia Birzeit Univ Dept Comp Sci Birzeit 72439 Palestine Natl Yunlin Univ Sci & Technol Coll Future Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Obuda Univ John von Neumann Fac Informat H-1034 Budapest Hungary Norwegian Univ Life Sci Sch Econ & Business N-1430 As Norway J Selye Univ Dept Informat Komarno 94501 Slovakia Oxford Brookes Univ Sch Built Environm Oxford OX3 0BP England 

出 版 物：《IEEE ACCESS》 (IEEE Access)

年 卷 期：2020年第8卷

页      面：225692-225702页

核心收录：

基　　金：Taif University Researchers Supporting Project, Taif University, Taif, Saudi Arabia [TURSP-2020/125] Guangdong University [2020KTSCX302] 

主　　题：Artificial neural networks Differential equations Convergence Licenses Machine learning algorithms Information technology Statistical analysis Machine learning artificial intelligence fuzzy systems Lyapunov stability learning algorithm multi-pantograph differential equations 

摘      要：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.