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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
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 
Submitted: December 20, 2011
Accepted: April 23, 2012
Published: 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.

Key words:  Fuzzy neural networks, smart grid, smart load forecaster, self-developing, self-adaptive, ,
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Cite this Reference:
Chinwang Lou and Mingchui Dong, . Intelligent Self-developing and Self-adaptive Electric Load Forecaster based on Adaptive FNN+GA+GD . Research Journal of Applied Sciences, Engineering and Technology, (20): 4012-4021.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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