Investigation of harmonic estimation using imperalist competitive algorithm method

Recently, some new methods and algorithms have been started to use as an alternative for harmonic estimation instead of Fourier Transform based traditional algorithms. Because, it is inevitable to look for alternative solutions for harmonic estimation problems due to the existing limitations of Fourier Transform based algorithms. The Imperialist Competitive Algorithm (ICA) investigated in this study is a social based intuitive optimization algorithm. The advantages of the evolutionary approximations selected by the nature have been suggested in genetic algorithms and its derivations in order to be useful in optimization area. The animal behaviors have been concluded as partial swarm and ant colony optimization algorithms. Recently, the animal behaviors simulate the human social behaviors and guide us to solve some engineering problems.