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2012 (Vol. 4, Issue: 20)
Article Information:

Intelligent Self-developing and Self-adaptive Electric Load Forecaster based on Adaptive FNN+GA+GD

Chinwang Lou and Mingchui Dong
Corresponding Author:  Chinwang Lou 

Key words:  Fuzzy neural networks, smart grid, smart load forecaster, self-developing, self-adaptive, ,
Vol. 4 , (20): 4012-4021
Submitted Accepted Published
December 20, 2011 April 23, 2012 October 15, 2012
Abstract:

In this study, a novel electric load forecaster based on adaptive Fuzzy Neural Networks (FNN) and using Genetic Algorithm (GA) mixed with Gradient Descent (GD) is proposed to make it to posses the human learning ability. The proposed SDSA-FNN is firstly compared with various methods applied on function approximations. Moreover, it is applied on electric load forecasting application and verified on electric load data recorded on Macao power system. The simulation results reveal that the proposed methodology not only keeps the traditional objective function.
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  Cite this Reference:
Chinwang Lou and Mingchui Dong, 2012. Intelligent Self-developing and Self-adaptive Electric Load Forecaster based on Adaptive FNN+GA+GD .  Research Journal of Applied Sciences, Engineering and Technology, 4(20): 4012-4021.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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