DocumentCode
2416263
Title
Application of Generalized Neuron Model in Short Term Load Forecasting under error functions
Author
Charan, C. Radha
Author_Institution
Sreenidhi Inst. of Sci. & Technol., Hyderabad, India
fYear
2010
fDate
29-31 July 2010
Firstpage
1
Lastpage
4
Abstract
Artificial Neural Networks (ANN´s) have large number of difficulties such as large training time, local minima error, large data etc. Generalized Neuron Model (GNM) overcomes the above drawbacks which specifically uses summation (Σ) and product (π). In this paper, the prediction of GNM to apply for Short Term Load Forecasting with different error functions with the results of root mean square error, maximum error, minimum error and time elapsed in seconds is presented.
Keywords
load forecasting; mean square error methods; neural nets; power engineering computing; artificial neural networks; error functions; generalized neuron model; local minima error; maximum error; minimum error; root mean square error; short term load forecasting; Adaptation model; Artificial neural networks; Load forecasting; Load modeling; Neurons; Predictive models; Testing; Artificial Neural Network; Error Functions; Generalized Neuron Model; Short Term Load Forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing Communication and Networking Technologies (ICCCNT), 2010 International Conference on
Conference_Location
Karur
Print_ISBN
978-1-4244-6591-0
Type
conf
DOI
10.1109/ICCCNT.2010.5591670
Filename
5591670
Link To Document