Click to open the HelpDesk interface
AECE - Front page banner



JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
SCOPUS CiteScore: 2.5
Issues per year: 4
Current issue: May 2021
Next issue: Aug 2021
Avg review time: 73 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


1,660,097 unique visits
Since November 1, 2009

Robots online now


SCImago Journal & Country Rank


Anycast DNS Hosting

 Volume 21 (2021)
     »   Issue 2 / 2021
     »   Issue 1 / 2021
 Volume 20 (2020)
     »   Issue 4 / 2020
     »   Issue 3 / 2020
     »   Issue 2 / 2020
     »   Issue 1 / 2020
 Volume 19 (2019)
     »   Issue 4 / 2019
     »   Issue 3 / 2019
     »   Issue 2 / 2019
     »   Issue 1 / 2019
 Volume 18 (2018)
     »   Issue 4 / 2018
     »   Issue 3 / 2018
     »   Issue 2 / 2018
     »   Issue 1 / 2018
 Volume 17 (2017)
     »   Issue 4 / 2017
     »   Issue 3 / 2017
     »   Issue 2 / 2017
     »   Issue 1 / 2017
  View all issues  


SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

Release of the v3 version of AECE Journal website. We moved to a new server and implemented the latest cryptographic protocols to assure better compatibility with the most recent browsers. Our website accepts now only TLS 1.2 and TLS 1.3 secure connections.

Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

Starting on the 15th of June 2020 we wiil introduce a new policy for reviewers. Reviewers who provide timely and substantial comments will receive a discount voucher entitling them to an APC reduction. Vouchers (worth of 25 EUR or 50 EUR, depending on the review quality) will be assigned to reviewers after the final decision of the reviewed paper is given. Vouchers issued to specific individuals are not transferable.

Starting on the 15th of December 2019 all paper authors are required to enter their SCOPUS IDs. You may use the free SCOPUS ID lookup form to find yours in case you don't remember it.

Read More »


  4/2018 - 7


Redesign of Morphing UAV for Simultaneous Improvement of Directional Stability and Maximum Lift/Drag Ratio

ARIK, S. See more information about ARIK, S. on SCOPUS See more information about ARIK, S. on IEEExplore See more information about ARIK, S. on Web of Science, TURKMEN, I. See more information about  TURKMEN, I. on SCOPUS See more information about  TURKMEN, I. on SCOPUS See more information about TURKMEN, I. on Web of Science, OKTAY, T. See more information about OKTAY, T. on SCOPUS See more information about OKTAY, T. on SCOPUS See more information about OKTAY, T. on Web of Science
Click to see author's profile in 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 (1,475 KB) | Citation | Downloads: 399 | Views: 1,430

Author keywords
unmanned aerial vehicles, stability, artificial intelligence, neural networks, optimization

References keywords
neural(9), optimization(8), design(7), technology(5), networks(5), aerospace(5), performance(4), oktay(4), morphing(4), lift(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 57 - 62
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04007
Web of Science Accession Number: 000451843400007
SCOPUS ID: 85058778064

Quick view
Full text preview
This paper presents a novel method based on the artificial intelligence to redesign of morphing Unmanned Aerial Vehicle (UAV) for improvement of index consisting of directional stability and maximum lift/drag (L/D) ratio. In this study, Artificial Neural Network (ANN) based objective function is optimized with Artificial Bee Colony (ABC) algorithm. Firstly, the sweep angle is selected as input parameter and directional stability and maximum L/D ratio are selected as output parameters for ANN. ANN is trained with a small number of data obtained by the computational fluid dynamics method and the trained ANN is used for multiplying these data. Two ABC optimization algorithms with different objective functions are used to improve the index consisting of directional stability and maximum L/D ratio: While the first is used the adjustment of the ANN weights, the second is used the optimization of the ANN based objective function. Simulation results realized with limited data show that although directional stability and maximum L/D ratio have inverse relation, they are optimized equally and simultaneously. Thus, the artificial intelligence techniques provide fast and accurate determination of the optimal aerodynamic shape of UAV without time consuming and complexity caused by theoretical calculations.

References | Cited By  «-- Click to see who has cited this paper

[1] J. Mariens, "Wing Shape Multidisciplinary Design Optimization," pp. 12-61, Master Thesis, Delft University of Technology, 2012.

[2] H. Yeo, W. Johnson, "Performance and Design Investigation of Heavy Lift Tilt-Rotor with Aerodynamic Interference Effects," Journal of Aircraft, vol. 46, no. 4, pp. 1231-1239, 2009.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 47]

[3] C. W. Jr. Acree, W. Johnson, "Performance, Loads and Stability of Heavy Lift Tiltrotors," in AHS Vertical Lift Aircraft Design Conference, San Francisco, CA, United States, 2006.

[4] W. Wisnoe, R. E. M. Nasir, W. Kuntjoro, A. M. I. Mamat, "Wind tunnel experiments and CFD analysis of Blended Wing Body (BWB) Unmanned Aerial Vehicle (UAV) at mach 0.1 and mach 0.3," in 13th International Conference on Aerospace Sciences & Aviation Technology, 2009, p. 14.

[5] S. Huang, L. Miller, J. Steck, "An exploratory application of neural networks to airfoil design," in 32nd Aerospace Sciences Meeting and Exhibit, American Institute of Aeronautics and Astronautics, 1994.

[6] T. Rajkumar, J. Bardina, "Prediction of Aerodynamic Coefficients Using Neural Networks for Sparse Data," in Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference, Pensacola Beach, Florida, USA, 2002, pp. 242-246.

[7] M. H. Djavareshkian, A. Esmaili, "Heuristic optimization of submerged hydrofoil using ANFIS-PSO," Ocean Engineering, vol. 92, pp. 55-63, 2014.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 13]

[8] A. Hacioglu, "Augmenting Genetic Algorithm with Neural Network and Implementation to the Inverse Airfoil Design," 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Multidisciplinary Analysis Optimization Conferences, 2004.

[9] A. Hacioglu, "Fast evolutionary algorithm for airfoil design via neural network," AIAA Journal, vol. 45, no. 9, pp. 2196-2203, 2007.
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 34]

[10] N. R. Secco, B. S. de Mattos, "Artificial neural networks to predict aerodynamic coefficients of transport airplanes," Aircraft Engineering and Aerospace Technology, vol. 89, no. 2, pp. 211-230, 2017.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 12]

[11] J. Brett, A. Ooi, "Effect of Sweep Angle on the Vertical Flow over Delta Wings at an Angle of Attack of 10°," Journal of Engineering Science and Technology, vol. 9, no. 6, pp. 768-781, 2014.

[12] R. C. Nelson, "Flight Stability and Automatic Control", pp. 67-71, WCB/McGraw Hill, 1998.

[13] D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Computer Engineering Department, Engineering Faculty, Erciyes University, Kayseri, Technical Report-TR06, 2005.

[14] D. Karaboga, B. Basturk, "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm," Journal of Global Optimization, vol. 39, no. 3, pp. 459-471, 2007.
[CrossRef] [Web of Science Times Cited 3601] [SCOPUS Times Cited 4495]

[15] D. R. Hush, B. G. Horne, "Progress in supervised neural networks," IEEE Signal Processing Magazine, vol. 10, no. 1, pp. 8-39, 1993.
[CrossRef] [Web of Science Times Cited 551] [SCOPUS Times Cited 905]

[16] S. Haykin, "Neural Networks: A Comprehensive Foundation", pp. 23-270, Macmillan, 1994.

[17] E. Oztemel, "Yapay Sinir Aglari", pp. 23-113, Papatya Bilim, 2003.

[18] L. H. Tsoukalas, R. E. Uhrig, "Fuzzy and neural approaches in engineering", pp. 191-229, Wiley, 1997.

[19] T. Oktay, S. Coban, "Simultaneous Longitudinal and Lateral Flight Control Systems Design for Both Passive and Active Morphing TUAVs," Elektronika ir Elektrotechnika, vol. 23, no. 5, pp. 15-20, 2017.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 10]

[20] T. Oktay, M. Konar, M. A. Mohamed, M. Aydin, F. Sal, M. Onay, M. Soylak, "Autonomous flight performance improvement of load-carrying unmanned aerial vehicles by active morphing," International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, vol. 10, no. 1, pp. 123-132, 2016.

[21] T. Oktay, S. Arik, I. Turkmen, M. Uzun, H. Çelik, "Neural network based redesign of morphing UAV for simultaneous improvement of roll stability and maximum lift/drag ratio," Aircraft Engineering and Aerospace Technology, 2018.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 10]

[22] T. Oktay, M. Uzun, "Aerodynamic Tailcone Shape Optimization for Autonomous Navigation Performance Maximization of Morphing Aerial Robot," presented at the International Conference on Engineering and Natural Science, Sarajevo, 2016.

References Weight

Web of Science® Citations for all references: 4,249 TCR
SCOPUS® Citations for all references: 5,526 TCR

Web of Science® Average Citations per reference: 185 ACR
SCOPUS® Average Citations per reference: 240 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-06-23 10:48 in 71 seconds.

Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2021
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: