A New Approach for Dynamic Stochastic Fractal Search with Fuzzy Logic for Parameter Adaptation

Stochastic fractal search (SFS) is a novel method inspired by the process of stochastic growth in nature and use mathematical concept. Considering chaotic diffusion property, an improved dynamic (DSFS) optimization algorithm presented. The DSFS was tested with benchmark functions, such as multimodal, hybrid, composite to evaluate performance parameter adaptation type-1 type-2 fuzzy inference models. main contribution article utilization logic fashion. This charge creating new particles, diversity iteration are input information used system control values diffusion.