Detail publikace

Předpověď týdenní spotřeby elektrické energie s využitím fuzzy neuronové sítě.

KHAN, M. ŽÁK, L. ONDRŮŠEK, Č.

Český název

Předpověď týdenní spotřeby elektrické energie s využitím fuzzy neuronové sítě.

Anglický název

FORECASTING WEEKLY ELECTRIC LOAD USING A HYBRID FUZZY-NEURAL NETWORK APPROACH

Typ

článek v časopise - ostatní, Jost

Jazyk

en

Originální abstrakt

A hybrid approach utilizing a fuzzy system and artificial neural network (ANN) for short-term load forecasting of the Czech Electric Power Company (ČEZ) is proposed in this paper. Expert knowledge represented by fuzzy rules is used for preprocessing input data fed to a neural network. For training the neural network for one-week ahead load forecasting, fuzzy ‘If-Then’ rules are used, in addition to historical load and temperature data that are usually employed in conventional supervised training algorithms. The fuzzy-neural network is trained on real data for the years 1994 through 1998 and evaluated on the data for the year 1999 for forecasting next-week load profiles. A very good prediction performance is attained as shown in the simulation results, which verify the effectiveness and superiority of the modeling technique.

Český abstrakt

Článek popisuje využití fuzzy neronové sítě pro předpověď spotřeby elektrické energie na další období.

Anglický abstrakt

A hybrid approach utilizing a fuzzy system and artificial neural network (ANN) for short-term load forecasting of the Czech Electric Power Company (ČEZ) is proposed in this paper. Expert knowledge represented by fuzzy rules is used for preprocessing input data fed to a neural network. For training the neural network for one-week ahead load forecasting, fuzzy ‘If-Then’ rules are used, in addition to historical load and temperature data that are usually employed in conventional supervised training algorithms. The fuzzy-neural network is trained on real data for the years 1994 through 1998 and evaluated on the data for the year 1999 for forecasting next-week load profiles. A very good prediction performance is attained as shown in the simulation results, which verify the effectiveness and superiority of the modeling technique.

Klíčová slova anglicky

One-week ahead load forecasting, Multilayer neural networks and Hybrid fuzzy-neural networks (FNN)

Rok RIV

2004

Vydáno

26.11.2001

ISSN

1210-2717

Časopis

Inženýrská mechanika - Engineering Mechanics

Ročník

2001

Číslo

8

Počet stran

55

BIBTEX


@article{BUT40535,
  author="Muhammad R {Khan} and Libor {Žák} and Čestmír {Ondrůšek},
  title="FORECASTING WEEKLY ELECTRIC LOAD USING A HYBRID FUZZY-NEURAL NETWORK APPROACH",
  journal="Inženýrská mechanika - Engineering Mechanics",
  year="2001",
  volume="2001",
  number="8",
  month="November",
  issn="1210-2717"
}