A comparative study using genetic algorithm and particle swarm optimization for lower order system modelling

• Autores: S. N. Sivanandam, S.N. Deepa
• Localización: International journal of the computer, the internet and management, ISSN 0858-7027, Vol. 17, Nº. 3 (SEP-DIC), 2009, págs. 1-10
• Idioma: inglés
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• Resumen

  • In recent years Evolutionary Computation has its growth to extent. Amidst various Evolutionary computation approaches, Genetic Algorithms and Particle swarm optimisation are used in optimisation problems. The two approaches find a solution to a given objective function employing different procedures and computational techniques; as a result their performance can be evaluated and compared. The problem area chosen is that of lower order system modelling used in control systems engineering. Particle Swarm Optimization and Genetic Algorithm obtains a better lower order approximant that reflects the characteristics of the original higher order system and the performance evaluated using these methods are compared. Integral square error is used as an indicator for selecting the lower order model.