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

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

Metaheuristic algorithms are widely used as optimization methods, due to their global exploration and exploitation characteristics, which obtain better results than a simple heuristic. The Stochastic Fractal Search (SFS) is a novel method inspired by the process of stochastic growth in nature and the use of the fractal mathematical concept. Considering the chaotic-stochastic diffusion property, an improved Dynamic Stochastic Fractal Search (DSFS) optimization algorithm is presented. The DSFS algorithm was tested with benchmark functions, such as the multimodal, hybrid and composite functions, to evaluate the performance of the algorithm with dynamic parameter adaptation with type-1 and type-2 fuzzy inference models. The main contribution of the article is the utilization of fuzzy logic in the adaptation of the diffusion parameter in a dynamic fashion. This parameter is in charge of creating new fractal particles, and the diversity and iteration are the input information used in the fuzzy system to control the values of diffusion.

Optical Analysis of Fractional Particles

Analysis of fractal particles, like sawdust or dust, by sieve method is rather difficult in terms of the measuring system and time-consuming at samples evaluation. The results give only partial information of the particle dimensions in an examinable sample. Modern optical methods of fractal particles analysis in the industry complexly acquaint with the sample; they provide information about the particle rate and size, average, maximum and minimum occurring dimension, particle surface, and shape composition of a sample. In our experiment were evaluated wood particles with IP camera IQEye 702. Camera captures the scene with sawdust and send video via ethernet. In program Matlab is in time captured in this video one picture, which is further processed and in it are found measured particles. Subsequently are measured required parameters of captured particles.

A computational approach to modeling chaff clouds consisting of fractal particles

A chaff cloud is an electronic countermeasure to radio frequency emitters. The cloud immerses a protected entity in a multitude of false targets by reradiating incident electromagnetic energy from millions of thin aluminized fibers, foil strips, or elements printed with conductive ink. The elements are cut to form resonant structures to match the principle threat frequencies, making them an effective reradiator. Empirically testing chaff clouds is technically challenging, costly, and time consuming. With an increased emphasis on chaff research comes the need to characterize cloud radar cross-section performance to expand existing knowledge and explore development opportunities for future technologies. This paper describes the computational methodology and results for analyzing standard dipole chaff clouds and Koch snowflakes as a possible new chaff element.