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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: 57 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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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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  1/2018 - 15

 HIGH-IMPACT PAPER 

Optimization of Charge/Discharge Coordination to Satisfy Network Requirements Using Heuristic Algorithms in Vehicle-to-Grid Concept

DOGAN, A. See more information about DOGAN, A. on SCOPUS See more information about DOGAN, A. on IEEExplore See more information about DOGAN, A. on Web of Science, BAHCECI, S. See more information about  BAHCECI, S. on SCOPUS See more information about  BAHCECI, S. on SCOPUS See more information about BAHCECI, S. on Web of Science, DALDABAN, F. See more information about  DALDABAN, F. on SCOPUS See more information about  DALDABAN, F. on SCOPUS See more information about DALDABAN, F. on Web of Science, ALCI, M. See more information about ALCI, M. on SCOPUS See more information about ALCI, M. on SCOPUS See more information about ALCI, M. on Web of Science
 
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Download PDF pdficon (1,247 KB) | Citation | Downloads: 1,201 | Views: 4,919

Author keywords
electric vehicles, genetic algorithms, heuristic algorithms, smart grids, optimization

References keywords
grid(33), power(31), electric(28), vehicle(23), vehicles(21), energy(21), charging(18), plug(16), systems(14), smart(14)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 121 - 130
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01015
Web of Science Accession Number: 000426449500015
SCOPUS ID: 85043247244

Abstract
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Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.


References | Cited By

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Cited-By CrossRef

[1] Thermal-Electrochemical Modeling and Analysis of Different Cathode-Anode pairs for Lithium-ion Battery, SHARMA, S., PANWAR, A. K., TRIPATHI, M. M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 21, 2021.
Digital Object Identifier: 10.4316/AECE.2021.03007
[CrossRef] [Full text]

[2] Application of Artificial Intelligence for EV Charging and Discharging Scheduling and Dynamic Pricing: A Review, Chen, Qin, Folly, Komla Agbenyo, Energies, ISSN 1996-1073, Issue 1, Volume 16, 2022.
Digital Object Identifier: 10.3390/en16010146
[CrossRef]

[3] Route Optimization of Electric Vehicle considering Soft Time Windows and Two Ways of Power Replenishment, Meng, Ming, Ma, Yun, Advances in Operations Research, ISSN 1687-9147, Issue , 2020.
Digital Object Identifier: 10.1155/2020/5612872
[CrossRef]

[4] Vehicle-to-X (V2X) implementation: An overview of predominate trial configurations and technical, social and regulatory challenges, Gschwendtner, Christine, Sinsel, Simon R., Stephan, Annegret, Renewable and Sustainable Energy Reviews, ISSN 1364-0321, Issue , 2021.
Digital Object Identifier: 10.1016/j.rser.2021.110977
[CrossRef]

[5] Intelligent Charging Control of Power Aggregator for Electric Vehicles Using Optimal Control, ALKAWAZ, A. N., KANESAN, J., MOHD KHAIRUDDIN, A. S., CHOW, C. O., SINGH, M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 21, 2021.
Digital Object Identifier: 10.4316/AECE.2021.04003
[CrossRef] [Full text]

[6] An overview of load frequency control for grid using various control techniques, Vinitha, JC, Rani, P Usha, IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, Issue 1, Volume 1258, 2022.
Digital Object Identifier: 10.1088/1757-899X/1258/1/012056
[CrossRef]

[7] Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs, Onishi, Viviani Caroline, Antunes, Carlos Henggeler, Trovão, João Pedro Fernandes, Energies, ISSN 1996-1073, Issue 8, Volume 13, 2020.
Digital Object Identifier: 10.3390/en13081884
[CrossRef]

[8] Analysis of the Media Directing Theory Based on Multimedia Technology from the Perspective of Communication Studies, Fan, Ruichan, Journal of Physics: Conference Series, ISSN 1742-6588, Issue 3, Volume 1648, 2020.
Digital Object Identifier: 10.1088/1742-6596/1648/3/032026
[CrossRef]

[9] V2G Şarj İstasyonlarının Optimum Konum ve Kapasitelerinin Gri Kurt Optimizasyon Algoritması ile Belirlenmesi, SARIDAĞ, Ömer, DOĞAN, Ahmet, Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi, ISSN 2458-7575, Issue 2, Volume 8, 2021.
Digital Object Identifier: 10.35193/bseufbd.916804
[CrossRef]

[10] Optimizing coordinated spatio-temporal control of electric vehicles for enhanced energy sharing and performance across building communities, Zhang, Linfeng, Alvarez, Edgar Mauricio Ocampo, Huang, Pei, Energy and Buildings, ISSN 0378-7788, Issue , 2024.
Digital Object Identifier: 10.1016/j.enbuild.2024.114167
[CrossRef]

[11] Economic and emission reduction benefits of the implementation of eVTOL aircraft with bi-directional flow as storage systems in islands and case study for Canary Islands, Velaz-Acera, Néstor, Álvarez-García, Javier, Borge-Diez, David, Applied Energy, ISSN 0306-2619, Issue , 2023.
Digital Object Identifier: 10.1016/j.apenergy.2022.120409
[CrossRef]

[12] Comparative Optimization Analysis of Ramp Rate Constriction Factor Based PSO and Electro Magnetism Based PSO for Economic Load Dispatch in Electric Power System, Maharana, Himanshu Shekhar, Dash, Saroj Kumar, 2019 International Conference on Applied Machine Learning (ICAML), ISBN 978-1-7281-3908-1, 2019.
Digital Object Identifier: 10.1109/ICAML48257.2019.00020
[CrossRef]

[13] Smart and Coordinated Charging Using Ensemble Model for Plug-in Electric Vehicle, Najem, Ali, Abdellatif, Abdallah, Kanesan, Jeevan, Khairuddin, Anis Salwa Mohd, Kairi, Muhammad Izhar, 2023 Innovations in Power and Advanced Computing Technologies (i-PACT), ISBN 979-8-3503-2518-8, 2023.
Digital Object Identifier: 10.1109/i-PACT58649.2023.10434577
[CrossRef]

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