Detail publikace

Implementation of Hybrid-Fuzzy Neural Network Approach for Short Term Hourly and Peak Load Forecasting Using Weather Parameters.

KHAN, M. ŽÁK, L. ONDRŮŠEK, Č.

Anglický název

Implementation of Hybrid-Fuzzy Neural Network Approach for Short Term Hourly and Peak Load Forecasting Using Weather Parameters.

Typ

Stať ve sborníku v databázi WoS či Scopus

Jazyk

en

Originální abstrakt

This paper presents the development and practical implementation of a hybrid fuzzy-neural network (FNN) technique, which combines neural network modeling, and techniques from fuzzy logic and fuzzy set theory for short-term hourly and peak load forecasting for the Czech Power Company (ČEZ), Czech Republic. The load has two distinct patterns: weekday and weekend-day patterns. The weekend-day pattern include Saturday, Sunday, and special days/holidays loads. Inputs to the FNN are past loads and past weather parameters i.e., temperature, humidity, wind-speed, and wind-chill and the output of the FNN is the load forecast for a given day. Simulation results are presented to illustrate the performance and applicability of this hybrid approach. This approach avoids complex mathematical calculations and training on many years of data, and is very simple to implement on a personal computer.

Vydáno

2001-06-01

Nakladatel

VUT FSI

Místo

Brno

ISBN

80-214-1894-X

Kniha

7th International Conference on Soft Computing.

Strany od–do

282–

Počet stran

6

BIBTEX


@inproceedings{BUT6352,
  author="Muhammad R {Khan} and Libor {Žák} and Čestmír {Ondrůšek}",
  title="Implementation of Hybrid-Fuzzy Neural Network Approach for Short Term Hourly and Peak Load Forecasting Using Weather Parameters.",
  booktitle="7th International Conference on Soft Computing.",
  year="2001",
  pages="6",
  publisher="VUT FSI",
  address="Brno",
  isbn="80-214-1894-X"
}