Fuzzy differential equations are used to model problems in science and engineering. For example, it is well known that knowledge of dynamical systems modeled by ordinary differential equations is often incomplete or vague. Whereas, fuzzy differential equations are an appropriate method for modeling dynamical systems under uncertainty and uncertainty. In this article, Seikkala derivative-based numerical techniques for solving fuzzy ordinary differential equations are discussed. A thorough error analysis follows a detailed discussion of a numerical approach based on the Runge-Kutta Method RK6. By resolving a few linear and nonlinear fuzzy Cauchy problems, and applied in MATLAB computer.

Topics
MATLAB, Numerical algorithms, Numerical methods, Knowledge, Engineers
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