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JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Aug 2024
Next issue: Nov 2024
Avg review time: 56 days
Avg accept to publ: 60 days
APC: 300 EUR


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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A Proposed Signal Reconstruction Algorithm over Bandlimited Channels for Wireless Communications, ASHOUR, A., KHALAF, A., HUSSEIN, A., HAMED, H., RAMADAN, A.
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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  3/2010 - 3

 HIGH-IMPACT PAPER 

A New Protection Scheme for High Impedance Fault Detection using Wavelet Packet Transform

GHAFFARZADEH, N. See more information about GHAFFARZADEH, N. on SCOPUS See more information about GHAFFARZADEH, N. on IEEExplore See more information about GHAFFARZADEH, N. on Web of Science, VAHIDI, B. See more information about VAHIDI, B. on SCOPUS See more information about VAHIDI, B. on SCOPUS See more information about VAHIDI, B. on Web of Science
 
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Download PDF pdficon (540 KB) | Citation | Downloads: 1,758 | Views: 6,781

Author keywords
artificial neural network, distribution networks, fault detection, high impedance fault, wavelet packet

References keywords
power(22), high(15), fault(15), impedance(14), detection(14), delivery(12), wavelet(6), distribution(6), system(4), networks(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-08-31
Volume 10, Issue 3, Year 2010, On page(s): 17 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.03003
Web of Science Accession Number: 000281805600003
SCOPUS ID: 77956620776

Abstract
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This paper proposed a novel technique to effectively discriminate between the HIF and the normal system operation events in distribution by combining a preprocessing module based on wavelet packet transform with an artificial neural network(ANN). Wavelet packet is firstly applied to extract of distinctive feature of current signals. Then this information is introduced to training ANN for identifying an HIF from the normal system operation events. The simulated results clearly show that the proposed technique can accurately identify the HIF in overhead distribution feeder.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 15
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Cited-By CrossRef

[1] An improved protection strategy based on PCC-SVM algorithm for identification of high impedance arcing fault in smart microgrids in the presence of distributed generation, Eslami, Mostafa, Jannati, Mohsen, Tabatabaei, S. Sepehr, Measurement, ISSN 0263-2241, Issue , 2021.
Digital Object Identifier: 10.1016/j.measurement.2021.109149
[CrossRef]

[2] Hi‐Z fault location identification on low voltage distribution systems using IoT‐based digital twin model computation, Pamulaparthy, Balakrishna, Digital Twins and Applications, ISSN 2995-5629, Issue 1, Volume 1, 2024.
Digital Object Identifier: 10.1049/dgt2.12009
[CrossRef]

[3] High impedance fault protection in transmission lines using a WPT-based algorithm, Mahari, Arash, Seyedi, Heresh, International Journal of Electrical Power & Energy Systems, ISSN 0142-0615, Issue , 2015.
Digital Object Identifier: 10.1016/j.ijepes.2014.12.022
[CrossRef]

[4] Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis, SU, H., LIU, Q., LI, J., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 11, 2011.
Digital Object Identifier: 10.4316/aece.2011.03009
[CrossRef] [Full text]

[5] Software Tool for Real-Time Power Quality Analysis, MIRON, A., CHINDRIS, M. D., CZIKER, A. C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.04021
[CrossRef] [Full text]

[6] Detection of high impedance faults using current transformers for sensing and identification based on features extracted using wavelet transform, Chen, Jichao, Phung, Toan, Blackburn, Trevor, Ambikairajah, Eliathamby, Zhang, Daming, IET Generation, Transmission & Distribution, ISSN 1751-8687, Issue 12, Volume 10, 2016.
Digital Object Identifier: 10.1049/iet-gtd.2016.0021
[CrossRef]

[7] Evolving neuro-fuzzy network for real-time high impedance fault detection and classification, Silva, Sergio, Costa, Pyramo, Santana, Marcio, Leite, Daniel, Neural Computing and Applications, ISSN 0941-0643, Issue 12, Volume 32, 2020.
Digital Object Identifier: 10.1007/s00521-018-3789-2
[CrossRef]

[8] Fault Detection and Localization in Transmission Lines with a Static Synchronous Series Compensator, REYES-ARCHUNDIA, E., GUARDADO, J. L., MORENO-GOYTIA, E. L., GUTIERREZ-GNECCHI, J. A., MARTINEZ-CARDENAS, F., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 15, 2015.
Digital Object Identifier: 10.4316/AECE.2015.03003
[CrossRef] [Full text]

[9] High impedance fault detection and identification based on pattern recognition of phase displacement computation, Ali, Mohd Syukri, Abu Bakar, Ab Halim, Tan, Chia Kwang, Arof, Hamzah, Mokhlis, Hazlie, IEEJ Transactions on Electrical and Electronic Engineering, ISSN 1931-4973, Issue 4, Volume 13, 2018.
Digital Object Identifier: 10.1002/tee.22600
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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