Application of Artificial Neural Networks and Fuzzy logic Methods for Short Term Load Forecasting-Reference-Cited by-同舟云学术

Application of Artificial Neural Networks and Fuzzy logic Methods for Short Term Load Forecasting

Published:2012 Issue: Volume:14 Page:1883-1888
ISSN:1876-6102
Container-title:Energy Procedia
language:en
Short-container-title:Energy Procedia

Author:

Badri A.,Ameli Z.,Birjandi A.Motie

Publisher

Elsevier BV

Reference11 articles.

1. Pradeepta Kumar Sarangi, Nanhay Singh, R.K. Chauhan and Raghuraj Singh. Short term Load Forecasting using Artifical Neural Network:A Comparison With Genetic Algoritm Implemention. ARPN Journal of Engineering and Applied Sciences; VOL. 4, NO. 9, NOVEMBER 2009.

2. Rashid Mohammed Roken, Masood A. Badri. Time Series Models for Forecasting Monthly Electricity Peak Load for Dubai. Chancellor's Undergraduate Research Award; 2006.

3. Amit Jain, B. Satish. Clustering based Short Term Load Forecasting using Support Vector Machines, roceedings of 2009 IEEE Bucharest PowerTech conference; IIIT/TR/2009.

4. Eugene A. Feinberg, Dora Genethliou. Load Forecasting, chapter 12; 2004.

5. Comparison of Very Short-Term Load Forecasting Techniques;Sub Barayan;IEEE Transactions on Power Systems,1996

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