A novel genetic-algorithm-based neural network for short-term load forecasting
Ling, S.H.
Leung, F.H.F.
Lam, H.K.
Yim-Shu Lee
Tam, P.K.S.
Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Aug. 2003
Volume: 50,
Issue: 4
On page(s): 793- 799
ISSN: 0278-0046
INSPEC Accession Number: 7708560
Digital Object Identifier: 10.1109/TIE.2003.814869
Current Version Published: 2003-07-28
Abstract
This paper presents a neural network with a novel neuron model. In this model, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. This neural network provides better performance than a traditional feedforward neural network, and fewer hidden nodes are needed. The parameters of the proposed neural network are tuned by a genetic algorithm with arithmetic crossover and nonuniform mutation. Some applications are given to show the merits of the proposed neural network.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
