Abstract
In a variety of engineering and science challenges, fuzzy nonlinear equations play a critical role. In this chapter, we present a gradient-based optimizer (GBO) technique for solving fuzzy nonlinear equations. To traverse the search space, the GBO employs two primary operators: the gradient search rule (GSR) and the local escaping operator (LEO), as well as a collection of vectors. The GSR uses a gradient-based approach to enhance the exploration tendency and speed up the convergence rate to attain optimal search space locations. The suggested GBO can escape local optima with the help of the LEO. We tested the novel algorithm’s ability to solve fuzzy nonlinear equations and results suggest the GBO is effective for solving fuzzy nonlinear equations due to its improved exploration abilities. We used MATLAB2009b to carry out the calculations in this study.
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