Click to open the HelpDesk interface
AECE - Front page banner



JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Feb 2018
Next issue: May 2018
Avg review time: 107 days


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

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


1,880,940 unique visits
Since November 1, 2009

No robots online now


SCImago Journal & Country Rank

SEARCH ENGINES - Google Pagerank


Anycast DNS Hosting

 Volume 18 (2018)
     »   Issue 1 / 2018
 Volume 17 (2017)
     »   Issue 4 / 2017
     »   Issue 3 / 2017
     »   Issue 2 / 2017
     »   Issue 1 / 2017
 Volume 16 (2016)
     »   Issue 4 / 2016
     »   Issue 3 / 2016
     »   Issue 2 / 2016
     »   Issue 1 / 2016
 Volume 15 (2015)
     »   Issue 4 / 2015
     »   Issue 3 / 2015
     »   Issue 2 / 2015
     »   Issue 1 / 2015
  View all issues  


Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

Read More »


  1/2017 - 1
View TOC | « Previous Article | Next Article »

Wind Power Prediction Based on LS-SVM Model with Error Correction

ZHANG, Y. See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on IEEExplore See more information about ZHANG, Y. on Web of Science, WANG, P., NI, T., CHENG, P., LEI, S. See more information about LEI, S. on SCOPUS See more information about LEI, S. on SCOPUS See more information about LEI, S. on Web of Science
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,180 KB) | Citation | Downloads: 953 | Views: 840

Author keywords
computer errors, error correction, support vector machines, power engineering computing, wind energy generation

References keywords
wind(19), energy(15), prediction(11), speed(10), wang(9), power(7), renewable(6), jrenene(6), term(5), short(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-02-28
Volume 17, Issue 1, Year 2017, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.01001
Web of Science Accession Number: 000396335900001
SCOPUS ID: 85014266751

Quick view
Full text preview
As conventional energy sources are non-renewable, the world's major countries are investing heavily in renewable energy research. Wind power represents the development trend of future energy, but the intermittent and volatility of wind energy are the main reasons that leads to the poor accuracy of wind power prediction. However, by analyzing the error level at different time points, it can be found that the errors of adjacent time are often approximately the same, the least square support vector machine (LS-SVM) model with error correction is used to predict the wind power in this paper. According to the simulation of wind power data of two wind farms, the proposed method can effectively improve the prediction accuracy of wind power, and the error distribution is concentrated almost without deviation. The improved method proposed in this paper takes into account the error correction process of the model, which improved the prediction accuracy of the traditional model (RBF, Elman, LS-SVM). Compared with the single LS-SVM prediction model in this paper, the mean absolute error of the proposed method had decreased by 52 percent. The research work in this paper will be helpful to the reasonable arrangement of dispatching operation plan, the normal operation of the wind farm and the large-scale development as well as fully utilization of renewable energy resources.

References | Cited By

Cited-By ISI Web of Science

Web of Science® Times Cited: 3 [View]
View record in Web of Science® [View]
View Related Records® [View]

Updated today

Cited-By CrossRef

SCOPUS® Times Cited: 2
View record in SCOPUS®
[Free preview]

Updated today

Cited-By CrossRef

[1] Wind energy prediction with LS-SVM based on Lorenz perturbation, Zhang, Yagang, Wang, Penghui, Zhang, Chenhong, Lei, Shuang, The Journal of Engineering, ISSN 2051-3305, Issue 13, Volume 2017, 2017.
Digital Object Identifier: 10.1049/joe.2017.0626

[2] Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance, ZHANG, Y., WANG, P., CHENG, P., LEI, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.03014
[CrossRef] [Full text]

Updated today

Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.

Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.

Copyright ©2001-2018
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.

Website loading speed and performance optimization powered by: