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Neural Computing and Applications
Published in: Neural Computing and Applications 9/2019

03-03-2018 | Original Article

System of type-2 fuzzy differential equations and its applications

Authors: Abhirup Bandyopadhyay, Samarjit Kar

Published in: Neural Computing and Applications | Issue 9/2019

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Abstract

This paper develops the mathematical framework and the solution of a system of type-2 fuzzy ordinary differential equations (T2FDE). The theory of T2FDEs is developed with type-2 fuzzy initial values, type-2 fuzzy boundary values and type-2 fuzzy parameters. Some natural phenomena can be modelled as dynamical systems whose initial conditions and/or parameters may be imprecise in nature. The imprecision of initial values and/or parameters is generally modelled by fuzzy sets. Here, the concept of generalized H2-differentiability, based on the extension of the class of differentiable type-2 fuzzy mappings or Hukuhara derivatives, is applied. Numerical simulations of type-2 fuzzy differential equations have also been developed. Several illustrative examples have been provided for different T2FDE models related to environmental dynamics and problems in mathematical biology.
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Metadata
Title
System of type-2 fuzzy differential equations and its applications
Authors
Abhirup Bandyopadhyay
Samarjit Kar
Publication date
03-03-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 9/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3380-x

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