Application of GRNN Neural Network in Short Term Load Forecasting

Kai Wang; Shuai Bin Huang; Yu Le Ding

doi:10.4028/www.scientific.net/AMR.971-973.2242

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 971-973Application of GRNN Neural Network in Short Term...

Application of GRNN Neural Network in Short Term Load Forecasting

Abstract:

According to the short-term power load has a strong feature of time series, based on the joint probability density theory, GRNN neural network model is introduced to solve the load forecasting problem. By comparison with actual examples and algorithm analysis of sensitivity, the method proposed in this thesis has high prediction accuracy and strong robustness.

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Periodical:

Advanced Materials Research (Volumes 971-973)

Pages:

2242-2247

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.971-973.2242

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Online since:

June 2014

Authors:

Kai Wang*, Shuai Bin Huang, Yu Le Ding

Keywords:

GRNN Neural Network, Joint Probability Density, Short Term Load Forecasting

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