An Application of Radial Basis Function Neural Network for Short Term Load Forecasting Solution

An Application of Radial Basis Function Neural Network for Short Term Load Forecasting Solution

This paper proposes an approach to solve short term load forecasting (STLF) problem by using radial basis function neural network (RBFNN). STLF is one of the main issues for power system scheduling since it can help the utility company to manage the generation of power system economically and reliab...

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Bibliographic Details
Main Authors: Nurul Faezah, Othman, Mohd Herwan, Sulaiman, Zuriani, Mustaffa
Format: Article
Language:English
Published: American Scientific Publisher 2018
Subjects:
QA76 Computer software
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/19950/
http://umpir.ump.edu.my/id/eprint/19950/
http://umpir.ump.edu.my/id/eprint/19950/
http://umpir.ump.edu.my/id/eprint/19950/1/39.%20An%20Application%20of%20Radial%20Basis%20Function%20Neural%20Network%20for%20Short%20Term%20Load%20Forecasting%20Solution1.pdf

Internet

http://umpir.ump.edu.my/id/eprint/19950/
http://umpir.ump.edu.my/id/eprint/19950/
http://umpir.ump.edu.my/id/eprint/19950/
http://umpir.ump.edu.my/id/eprint/19950/1/39.%20An%20Application%20of%20Radial%20Basis%20Function%20Neural%20Network%20for%20Short%20Term%20Load%20Forecasting%20Solution1.pdf

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