Superfast autoconfiguring artificial neural networks and their application to power systems-Reference-Cited by-同舟云学术

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Superfast autoconfiguring artificial neural networks and their application to power systems

Published:1995-10 Issue:1 Volume:35 Page:11-16
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Novak Bojan

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference31 articles.

1. The Organization of Behavior;Hebb,1949

2. Introduction to the Theory of Neural Computation;Hertz,1991

3. Short term load forecasting using a multilayer neural network with an adaptive learning algorithm;Ho;IEEE Trans. Power Syst.,1992

4. Applications of neural networks to power systems;Mori,1993

5. A two phase method for a short-term load forecasting;Novak,1993

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. Cyclic electric load forecasting by seasonal SVR with chaotic genetic algorithm;International Journal of Electrical Power & Energy Systems;2013-01

3. Introduction;Lecture Notes in Energy;2013

4. Application of echo state networks in short-term electric load forecasting;Energy;2012-03

5. A computational intelligence scheme for the prediction of the daily peak load;Applied Soft Computing;2011-12

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