Improved Chaos Game Optimization (ICGO)

ICGO is an enhanced version of the Chaos Game Optimization (CGO)
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Updated 13 Jun 2024

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ICGO is an enhanced version of the Chaos Game Optimization (CGO) algorithm, with improvements made to the mutation phase of the traditional CGO method. The foundational mathematics of CGO is rooted in the self-resemblance properties of fractals in chaos theory and the fundamental principles of creating the Sierpinski triangle. The Sierpinski triangle is crafted by segmenting each equilateral triangle into three smaller triangles, each having half the edge length of the original. When the count of initial fractal vertices rises to N, a Sierpinski triangle of N − 1 dimensions can be established,

Cite As

Mehrabi Hashjin, Nastaran, et al. “Novel Hybrid Classifier Based on Fuzzy Type-III Decision Maker and Ensemble Deep Learning Model and Improved Chaos Game Optimization.” Cluster Computing, Springer Science and Business Media LLC, May 2024, doi:10.1007/s10586-024-04475-7.

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MATLAB Release Compatibility
Created with R2024a
Compatible with any release
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Version Published Release Notes
1.0.1

Please check the paper.

1.0.0