Analysis of Scalability and Sensitivity for Chaotic Sine Cosine Algorithms | Zendy

Dunia Tahir | Zendy; Ramzy S. Ali | Zendy

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Analysis of Scalability and Sensitivity for Chaotic Sine Cosine Algorithms

Author(s) -

Dunia Tahir,

Ramzy S. Ali

Publication year - 2018

Publication title -

iraqi journal for electrical and electronic engineering

Language(s) - English

Resource type - Journals

eISSN - 2078-6069

pISSN - 1814-5892

DOI - 10.37917/ijeee.14.2.6

Subject(s) - sine , chaotic , algorithm , discrete cosine transform , trigonometric functions , mathematics , sensitivity (control systems) , sine and cosine transforms , scalability , computer science , artificial intelligence , mathematical analysis , electronic engineering , geometry , engineering , image (mathematics) , fourier analysis , short time fourier transform , fourier transform , database

Chaotic Sine-Cosine Algorithms (CSCAs) are new metaheuristic optimization algorithms. However, Chaotic Sine-Cosine Algorithm (CSCAs) are able to manipulate the problems in the standard Sine-Cosine Algorithm (SCA) like, slow convergence rate and falling into local solutions. This manipulation is done by changing the random parameters in the standard Sine-Cosine Algorithm (SCA) with the chaotic sequences. To verify the ability of the Chaotic Sine-Cosine Algorithms (CSCAs) for solving problems with large scale problems. The behaviors of the Chaotic Sine-Cosine Algorithms (CSCAs) were studied under different dimensions 10, 30, 100, and 200. The results show the high quality solutions and the superiority of all Chaotic Sine-Cosine Algorithms (CSCAs) on the standard SCA algorithm for all selecting dimensions. Additionally, different initial values of the chaotic maps are used to study the sensitivity of Chaotic Sine-Cosine Algorithms (CSCAs). The sensitivity test reveals that the initial value 0.7 is the best option for all Chaotic Sine-Cosine Algorithms (CSCAs).

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