The estimation of electric power losses in electrical networks by fuzzy regression model using genetic algorithm.

@article{Mogilenko2004,
abstract = {This paper presents the comparative study for fuzzy regression model using linear programming, fuzzy regression model using genetic algorithms and standard regression model. The fuzzy and standard models were developed for estimation of electric power losses in electrical networks. Simulation was carried out with a tool developed in MATLAB.},
author = {Mogilenko, A. V., Pavlyuchenko, D. A.},
journal = {Mathware and Soft Computing},
keywords = {Redes eléctricas; Potencia eléctrica; Estimación; Lógica difusa; Análisis de regresión; Algoritmos genéticos; fuzzy regression; membership function; genetic algorithms; electrical networks; electric power losses},
language = {eng},
number = {1},
pages = {13-30},
title = {The estimation of electric power losses in electrical networks by fuzzy regression model using genetic algorithm.},
url = {http://eudml.org/doc/39272},
volume = {11},
year = {2004},
}

TY - JOUR
AU - Mogilenko, A. V.
AU - Pavlyuchenko, D. A.
TI - The estimation of electric power losses in electrical networks by fuzzy regression model using genetic algorithm.
JO - Mathware and Soft Computing
PY - 2004
VL - 11
IS - 1
SP - 13
EP - 30
AB - This paper presents the comparative study for fuzzy regression model using linear programming, fuzzy regression model using genetic algorithms and standard regression model. The fuzzy and standard models were developed for estimation of electric power losses in electrical networks. Simulation was carried out with a tool developed in MATLAB.
LA - eng
KW - Redes eléctricas; Potencia eléctrica; Estimación; Lógica difusa; Análisis de regresión; Algoritmos genéticos; fuzzy regression; membership function; genetic algorithms; electrical networks; electric power losses
UR - http://eudml.org/doc/39272
ER -