Wavelet‐artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems-Reference-Cited by-同舟云学术

Wavelet‐artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems

Published:2015-08 Issue:11 Volume:9 Page:1104-1111
ISSN:1751-8695
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Lima Fernando P.A.¹,Lotufo Anna Diva P.¹,Minussi Carlos Roberto¹

Affiliation:

1. Electrical Engineering DepartmentFaculty of Engineering of Ilha SolteiraUNESP, Universidade Estadual Paulista ‘Júlio de Mesquita Filho’Av. Brasil 56, P.O. Box 31Ilha SolteiraSP15385‐000Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2014.1102

Reference30 articles.

1. Electric Power Substations Engineering

2. A methodology for intelligent sensor measurement, validation, fusion, and fault detection for equipment monitoring and diagnostics

3. Power quality disturbance waveform recognition using wavelet-based neural classifier. I. Theoretical foundation

4. Benmokhtar R. Huet B.: ‘Neural network combining classifier based on Dempster–Shafer theory’.Proc. of the Int. Multi Conf. on Computer Science and Information Technology 2006 pp.3–10

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