Open AccessDigital design and optimization of higher order adaptive system using Continuous genetic algorithm
Author(s) -
Vijay Kumar Yadav,
Sarita Singh Bhadauria
Publication year - 2012
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v1i4.186
Subject(s) - crossover , genetic algorithm , rate of convergence , mathematical optimization , convergence (economics) , meta optimization , continuous optimization , algorithm , selection (genetic algorithm) , computer science , rank (graph theory) , operator (biology) , quality control and genetic algorithms , mathematics , optimization problem , multi swarm optimization , artificial intelligence , key (lock) , computer security , repressor , economic growth , chemistry , biochemistry , transcription factor , combinatorics , economics , gene
An algorithm for design and optimization of higher order adaptive system are presented in this paper. In this work, the algorithm applied on the continuous search space parameter rather than discrete search space parameter. A new continuous genetic operator such that Rank based selection, Normal crossover and mutations are used to improve the rate of convergence and solution quality has been proposed.