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Machine Learning for Modeling the Singular Multi-Pantograph Equations

Authors: Amirhosein Mosavi; Manouchehr Shokri; Zulkefli Mansor; Sultan Noman Qasem; Shahab S. Band; Ardashir Mohammadzadeh;
APC: 1,717.88 EUR

Machine Learning for Modeling the Singular Multi-Pantograph Equations

Abstract

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.

Country
Germany
Keywords

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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    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Average
Top 10%
Green
gold