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Please use this identifier to cite or link to this item: http://tainguyenso.vnu.edu.vn/jspui/handle/123456789/12639

Title: Hopfield network and parallel genetic algorithm for solving state estimate in power systems
Authors: Khoa T.Q.D.
Binh P.T.T.
Khoa T.V.
Keywords: Genetic algorithms
Neural network
State estimation
Issue Date: 2004
Publisher: 2004 International Conference on Power System Technology, POWERCON 2004
Citation: Volume 1, Issue , Page 845-849
Abstract: In power systems, the state estimation computation takes an important role in security controls and the weighted least squares (WLS) method has been widely used at present This paper presents the artificial neural network for static state estimation. Hopfield neural network (HNN) and Parallel Genetic Algorithms (PGA) are employed to solve static state estimation on the 5 bus system. © 2004 IEEE.
URI: http://tainguyenso.vnu.edu.vn/jspui/handle/123456789/12639
ISSN: 
Appears in Collections:Articles of Universities of Vietnam from Scopus

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