Detail publikačního výsledku

Fuzzy model optimization by a genetic algorithm

HAMMER, M.

Originální název

Fuzzy model optimization by a genetic algorithm

Anglický název

Fuzzy model optimization by a genetic algorithm

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The lifetime of the insulating system of electric rotary machines is strongly dependet upon electrical and thermal features of the insulating material used. The subject of the diagnostic is to specify the condition of insulation used. At present days, the most popular diagnostic tools are the methods of artifical inteligence, and one mothod is the fuzzy modeling. However, this tool has many variable parameters, and the resulting efect is dependent upon on the suitable setting. This paper is concentrated on the use of genetic algorithms for the optimization of variable parameters in the fuzzy model that is used as a diagnostic tool for winding insulation of electric rotary machines. In this case, the optimization of fuzzy model means the minimize the mean absolute error for the diagnostics of winding insulation. The first section of the paper describes the architecture and the setting of the generic algorithm, the fuzzy model optimization and the input output data. The second section presents the optimization curves, and the calculated values that were specifed by the genetic algorithm as the optimized ones are shown in tables. The use of the diagnostic tool to solve the problems investigated is assessed in tables. The optimization method,the genetic algorithm and the fuzzy model were programmed in Matlab 6 enviroment. Also, all simulations and the calculated values were obtained by means of this product.

Anglický abstrakt

The lifetime of the insulating system of electric rotary machines is strongly dependet upon electrical and thermal features of the insulating material used. The subject of the diagnostic is to specify the condition of insulation used. At present days, the most popular diagnostic tools are the methods of artifical inteligence, and one mothod is the fuzzy modeling. However, this tool has many variable parameters, and the resulting efect is dependent upon on the suitable setting. This paper is concentrated on the use of genetic algorithms for the optimization of variable parameters in the fuzzy model that is used as a diagnostic tool for winding insulation of electric rotary machines. In this case, the optimization of fuzzy model means the minimize the mean absolute error for the diagnostics of winding insulation. The first section of the paper describes the architecture and the setting of the generic algorithm, the fuzzy model optimization and the input output data. The second section presents the optimization curves, and the calculated values that were specifed by the genetic algorithm as the optimized ones are shown in tables. The use of the diagnostic tool to solve the problems investigated is assessed in tables. The optimization method,the genetic algorithm and the fuzzy model were programmed in Matlab 6 enviroment. Also, all simulations and the calculated values were obtained by means of this product.

Klíčová slova

Fuzzy

Klíčová slova v angličtině

Fuzzy

Autoři

HAMMER, M.

Vydáno

01.01.2003

Nakladatel

TECOS

Místo

Slovenia

ISBN

961-90401-7-1

Kniha

ICIT 2003 4th Internationl conference on Industrial Tools

Strany od

377

Strany počet

4

BibTex

@inproceedings{BUT13332,
  author="Miloš {Hammer}",
  title="Fuzzy model optimization by a genetic algorithm",
  booktitle="ICIT 2003 4th Internationl conference on Industrial Tools",
  year="2003",
  pages="4",
  publisher="TECOS",
  address="Slovenia",
  isbn="961-90401-7-1"
}