Publication detail

FUZZY-NEURAL NETWORK BASED SHORT-TERM SEASONAL AND AVERAGE LOAD FORECASTING

KHAN, M. ŽÁK, L. ONDRŮŠEK, Č.

English title

FUZZY-NEURAL NETWORK BASED SHORT-TERM SEASONAL AND AVERAGE LOAD FORECASTING

Type

Paper in proceedings (conference paper)

Language

en

Original abstract

A hybrid approach utilizing a fuzzy system and artificial neural network for short-term average and seasonal load prediction is proposed for the Czech Electric Power Utility (ČEZ), Czech Republic in this paper. The FNN is trained on real data and evaluated for forecasting seasonal and average load profiles based on forecast weather data. The fuzzy membership values of the load and weather variables are the inputs to the hybrid fuzzy-neural network (FNN) and the output is the predicted load. The performance of this network has been compared with ANN technique in order to demonstrate the superiority of this approach.

Released

2001-09-25

Publisher

n

Location

Zlín

ISBN

80-7318-030-8

Book

4th International Conference on Prediction and Nonlinear Dynamics, Nostradamus Prediction Conference

Pages from–to

13–

Pages count

1

BIBTEX


@inproceedings{BUT3902,
  author="Muhammad R {Khan} and Libor {Žák} and Čestmír {Ondrůšek}",
  title="FUZZY-NEURAL NETWORK BASED SHORT-TERM SEASONAL AND AVERAGE LOAD FORECASTING",
  booktitle="4th International Conference on Prediction and Nonlinear Dynamics, Nostradamus Prediction Conference",
  year="2001",
  pages="1",
  publisher="n",
  address="Zlín",
  isbn="80-7318-030-8"
}