| 1/2018 - 15 |
Optimization of Charge/Discharge Coordination to Satisfy Network Requirements Using Heuristic Algorithms in Vehicle-to-Grid ConceptDOGAN, A.   , BAHCECI, S. , DALDABAN, F. , ALCI, M. |
View the paper record and citations in  |
| Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science |
Download PDF  (1,247 KB) | Citation | Downloads: 1,079 | Views: 4,446 |
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
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 «-- Click to see who has cited this paper |
| [1] U.S. Energy Administration Office, International Energy Outlook, Washington, DC, USA, DOE/EIA-0484(2016), May 2016. [Online] Available: Temporary on-line reference link removed - see the PDF document
[2] Electric Power Research Institute, Environmental assessment of plug-in hybrid electric vehicles. Volume 1: Nationwide Greenhouse Gas Emissions, CA, USA, 1015325, July 2007. [Online] Available: Temporary on-line reference link removed - see the PDF document [3] International Energy Agency. Global EV Outlook 2017 Two million and counting. Paris, FR, OECD/IEA 2017, July 2017. [Online] Available: Temporary on-line reference link removed - see the PDF document [4] X. Fang, S. Misra, G. Xue, and D. Yang, "Smart Grid The New and Improved Power Grid: A Survey ," IEEE Commun. Surveys Tuts., vol. 14, no. 4, pp. 944980, 2012. [CrossRef] [Web of Science Times Cited 1818] [SCOPUS Times Cited 2358] [5] S. Xie, W. Zhong, K. Xie, R. Yu, and Y. Zhang, "Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming," IEEE Trans. Neural Netw. Learn. Syst., vol. 27, no. 8, pp. 16971707, 2016. [CrossRef] [Web of Science Times Cited 82] [SCOPUS Times Cited 84] [6] E. De Caluwe, Grid-supportive charging infrastructure for plug-in electric vehicles, PhD thesis, K.U.Leuven, Faculty of Engineering Science, 2015. [Online] Available: Temporary on-line reference link removed - see the PDF document [7] J. Taylor, A. Maitra, M. Alexander, D. Brooks, and M. Duvall, "Evaluation of the impact of plug-in electric vehicle loading on distribution system operations," in Proc. IEEE Power Energy Soc. Gen. Meet., Calgary, Canada, 26-30 July 2009 pp. 16. [CrossRef] [SCOPUS Times Cited 382] [8] M. J. Scott, M. K. Meyers, D. B. Elliott, W. M. Warwick, "Impacts Assessment of Plug-in Hybrid Vehicles on Electric Utilities and Regional US Power Grids Part 2: Economic Assessment," Pacific Northwest Nat. Lab., Richland, WA., DE-AC05-76RL01830, Nov. 2017 [Online] Available: Temporary on-line reference link removed - see the PDF document [9] A. Dogan, M. Kuzlu, M. Pipattanasomporn, S. Rahman, and T. Yalcinoz, "Impact of EV charging strategies on peak demand reduction and load factor improvement," in Proc. Inter. Conf. on Elect.l and Electronics Eng., Bursa, Turkey, 26-28 Nov. 2015, pp. 374-378. [CrossRef] [SCOPUS Times Cited 26] [10] C. Guille and G. Gross, "A conceptual framework for the vehicle-to-grid ( V2G ) implementation," Energy Policy, vol. 37, no. 11, pp. 43794390, 2009. [CrossRef] [Web of Science Times Cited 584] [SCOPUS Times Cited 795] [11] M. Yilmaz and P. T. Krein, "Review of the impact of vehicle-to-grid technologies on distribution systems and utility interfaces," IEEE Trans. Power Electron., vol. 28, no. 12, pp. 56735689, Dec. 2013. [CrossRef] [Web of Science Times Cited 616] [SCOPUS Times Cited 777] [12] C. S. Antunez, J. F. Franco, M. J. Rider, R. Romero, "A New Methodology for the Optimal Charging Coordination of Electric Vehicles Considering Vehicle-to-Grid Technology," IEEE Trans. Sustain. Energy. vol. 7, no. 2, pp. 596607, 2016. [CrossRef] [Web of Science Times Cited 53] [SCOPUS Times Cited 73] [13] K. Clement-nyns, E. Haesen, and J. Driesen, "The impact of vehicle-to-grid on the distribution grid," Electr. Power Syst. Res., vol. 81, no. 1, pp. 185192, 2011. [CrossRef] [Web of Science Times Cited 279] [SCOPUS Times Cited 359] [14] H. Liu, Z. Hu, Y. Song, and J. Lin, "Decentralized vehicle-to-grid control for primary frequency regulation considering charging demands," IEEE Trans. Power Syst., vol. 28, no. 3, pp. 34803489, Aug. 2013. [CrossRef] [Web of Science Times Cited 325] [SCOPUS Times Cited 431] [15] C. D. White and K. M. Zhang, "Using vehicle-to-grid technology for frequency regulation and peak-load reduction," J. Power Sources, vol. 196, no. 8, pp. 39723980, 2011. [CrossRef] [Web of Science Times Cited 210] [SCOPUS Times Cited 278] [16] Z. Wang and S. Wang, "Grid Power Peak Shaving and Valley Filling Using Vehicle-to-Grid Systems," IEEE Trans. Power Del., vol. 28, no. 3, pp. 18221829, 2013. [CrossRef] [Web of Science Times Cited 240] [SCOPUS Times Cited 289] [17] M. Brenna, F. Foiadelli, and M. Longo, "The Exploitation of Vehicle-to-Grid Function for Power Quality Improvement in a Smart Grid," IEEE Intell. Transp. Syst. vol. 15, no. 5, pp. 21692177, 2014. [CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 54] [18] H. Liu, Z. Hu, Y. Song, J. Wang, and X. Xie, "Vehicle-to-Grid Control for Supplementary Frequency Regulation Considering Charging Demands," IEEE Trans. Power Syst., vol. 30, no. 6, pp. 31103119, 2015. [CrossRef] [Web of Science Times Cited 177] [SCOPUS Times Cited 219] [19] M. Kesler, M. C. Kisacikoglu, and L. M. Tolbert, "Vehicle-to-Grid Reactive Power Operation Using Plug-In Electric Vehicle Bidirectional Offboard Charger," IEEE Ind. Electron., vol. 61, no. 12, pp. 67786784, 2014. [CrossRef] [Web of Science Times Cited 206] [SCOPUS Times Cited 259] [20] J. Lin, S. Member, K. Leung, V. O. K. Li, and A. In, "Optimal Scheduling With Vehicle-to-Grid Regulation Service," IEEE Internet Things J., vol. 1, no. 6, pp. 556569, 2014. [CrossRef] [Web of Science Times Cited 86] [SCOPUS Times Cited 103] [21] X. Wu, L. Li, J. Zou, and G. Zhang, "EV-Based Voltage Regulation in Line Distribution Grid." IEEE Instr. and Meas. Tech. Conf. Taipei 2016. [CrossRef] [SCOPUS Times Cited 10] [22] A. Andreotti, G. Carpinelli, F. Mottola, and D. Proto, "A review of single-objective optimization models for plug-in vehicles operation in smart grid- Part I: Theoretical aspects," in Proc. Power and Energy Society General Meeting, San Diego, USA, 22-26 July 2012, pp. 1-8 [CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 26] [23] A. Andreotti, G. Carpinelli, F. Mottola, and D. Proto "A review of single-objective optimization models for plug-in vehicles operation in smart grids part ii: Numerical applications to vehicles fleets," in Proc. Power and Energy Society General Meeting, San Diego, USA, 22-26 July 2012, pp. 1-8. [CrossRef] [SCOPUS Times Cited 23] [24] X. Bai, W. Qiao, "Robust optimization for bidirectional dispatch coordination of large-scale V2G," IEEE Trans Smart Grid, vol. 6, no. 4, pp. 19441954, 2015. [CrossRef] [Web of Science Times Cited 87] [SCOPUS Times Cited 94] [25] W. Qi, Z. Xu , Z-J. Shen, Hu Z, Song Y. "Hierarchical coordinated control of plug- in electric vehicles charging in multifamily dwellings,"IEEE Trans Smart Grid, vol. 5, no. 3, pp. 14651474, 2014. [CrossRef] [Web of Science Times Cited 77] [SCOPUS Times Cited 107] [26] C. Jin, , J. Tang, and P. Ghosh, "Optimizing Electric Vehicle Charging: A Customer's Perspective," IEEE Trans. Veh. Technol., vol. 62, no. 7, pp. 29192927, 2013. [CrossRef] [Web of Science Times Cited 178] [SCOPUS Times Cited 222] [27] A. H. Hajimiragha, C. A. Canizares, M. W. Fowler, S. Moazeni, and A. Elkamel, "A robust optimization approach for planning the transition to plug-in hybrid electric vehicles," IEEE Trans. Power Syst, vol. 26, no. 4, pp. 22642274, 2011. [CrossRef] [Web of Science Times Cited 124] [SCOPUS Times Cited 140] [28] K. Zhang, L. Xu, M. Ouyang, H. Wang, L. Lu, J. Li, "Optimal decentralized valley-filling charging strategy for electric vehicles,"Energy Convers Manag., vol. 78, no. 57, pp. 537550, 2009. [CrossRef] [Web of Science Times Cited 119] [SCOPUS Times Cited 129] [29] X. Wang, Q. Liang, "Energy management strategy for plug-in hybrid electric vehicles via bidirectional vehicle-to-grid," IEEE Syst J, vol. 37, no. 3, pp. 1789 - 1798, 2017. [CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 70] [30] M. Shafie-khah, M. P. Moghaddam, M. K. Sheikh-El-Eslami, M. Rahmani- Andebili, "Modeling of interactions between market regulations and behavior of plug-in electric vehicle aggregators in a virtual power market environment," Energy, vol. 40, no. 1, pp. 139-150, 2012. [CrossRef] [Web of Science Times Cited 70] [SCOPUS Times Cited 75] [31] Z. Yang, K. Li , A. Foley, C. Zhang, "Optimal Scheduling Methods to Integrate Plug-in Electric Vehicles with the Power System: A Review," in Proc. 19th IFAC World Congress, Cape Town, South Africa, 24-29 August 2014. [CrossRef] [SCOPUS Times Cited 23] [32] Z. Yang, K. Li , A. Foley, "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, vol. 51, no. 28, pp. 396-416, 2015. [CrossRef] [Web of Science Times Cited 148] [SCOPUS Times Cited 176] [33] Y. Sugii, K. Tsujino, T. Nagano, "A Genetic-Algorithm based scheduling method of charging of electric vehicles," in Proc. IEEE Systems, Man, and Cybernetics, Conference Proceedings, Tokyo, Japan, 12-15 Oct. 1999, pp. 1-8. [CrossRef] [34] G. Celli, E. Ghiani, F. Pilo, G. Pisano, G. G. Soma, "Particle Swarm Optimization for Minimizing the Burden of Electric Vehicles in Active Distribution Networks," in Proc. Power and Energy Society General Meeting, in Proc. Power and Energy Society General Meeting, San Diego, USA, 22-26 July 2012, pp. 1-7. [CrossRef] [SCOPUS Times Cited 36] [35] S. Xu, D. Feng, Z. Yan, L. Zhang, N. Li, L. Jing, J. Wang, "Ant-Based Swarm Algorithm for Charging Coordination of Electric Vehicles," Int. J. Dist. Sensor Network, vol. 9, no. 5, pp. 113, 2013. [CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 45] [36] I. Rahman, P. Vasant, B. S. M. Singh, M. Abdullah-Al-WadudHybrid, "Swarm Intelligence-Based Optimization for Charging Plug-in Hybrid Electric Vehicle," In: Nguyen N., Trawinski B., Kosala R. (eds) Intelligent Information and Database Systems. ACIIDS 2015. Lecture Notes in Computer Science, vol 9012. Springer, Cham [CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 7] [37] M. Alonso, H. Amaris, J. G. Germain, J. M. Galan, Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms," Energies, vol. 7, no. 4, pp. 2449-2475, 2014. [CrossRef] [Web of Science Times Cited 143] [SCOPUS Times Cited 168] [38] C. Jin, J. Tang, P. Ghosh, "Optimizing electric vehicle charging with energy storage in the electricity market," IEEE Trans Smart Grid, vol. 4, no. 1, pp. 311-320, 2013. [CrossRef] [Web of Science Times Cited 189] [SCOPUS Times Cited 210] [39] S. Shao, M. Pipattanasomporn, and S. Rahman, "Challenges of PHEV penetration to the residential distribution network," in Proc. IEEE Power Energy Soc. Gen. Meeting, 2009, Calgary, Canada, 26-30 July 2009, pp. 18. [CrossRef] [SCOPUS Times Cited 347] [40] C. D. White and K. M. Zhang, "Using vehicle-to-grid technology for frequency regulation and peak-load reduction," J. Power Sources, vol. 196, no. 8, pp. 3972-3980, 2011. [CrossRef] [Web of Science Times Cited 210] [SCOPUS Times Cited 278] [41] P. Richardson, D. Flynn, A. Keane, "Optimal Charging of Electric Vehicles in Low-Voltage Distribution Systems," IEEE Trans. Power Syst., vol. 27, no. 1, pp. 268 - 279, 2012. [CrossRef] [Web of Science Times Cited 373] [SCOPUS Times Cited 483] [42] S. Deilami, A. S. Masoum, P. S. Moses, M. A. S. Masoum, "Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile," IEEE Trans. Smart Grid, vol. 2, no. 3, pp. 456 - 467, 2011. [CrossRef] [Web of Science Times Cited 739] [SCOPUS Times Cited 946] [43] N. Banol A., J. F. Franco, M. Lavorato, M. J. Rider, R. Romero, "Plug-In Electric Vehicle Charging Coordination in Electrical Distribution Systems Using a Tabu Search Algorithm," IEEE 15th Int. Conf. Environment and Electrical Engineering (EEEIC), Rome, Italy, 10-13 June 2015, pp. 1-6. [CrossRef] [SCOPUS Times Cited 5] [44] O. Sundstrom, C. Binding, "Flexible Charging Optimization for Electric Vehicles Considering Distribution Grid Constraints," IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 26 - 37, 2011. [CrossRef] [Web of Science Times Cited 356] [SCOPUS Times Cited 472] [45] A. Dogan, T. Yalcinoz, M. Alci, "A Comparison of Heuristic Methods for Optimum Power Flow Considering Valve Point Effect", Elektronika Ir Elektrotechnika, vol. 22, no.5, pp.32-37, 2016. [CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 11] [46] P. Richardson, D. Flynn, and A. Keane, "Optimal charging of electric vehicles in low-voltage distribution systems," IEEE Trans. Power Syst., vol. 27, no. 1, pp. 268279, 2012. [CrossRef] [Web of Science Times Cited 373] [SCOPUS Times Cited 483] [47] C. Wu and H. Mohsenian-rad, "Vehicle-to-Aggregator Interaction Game," IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 434442, 2012. [CrossRef] [Web of Science Times Cited 298] [SCOPUS Times Cited 339] [48] H. Liang, B. J. Choi, and W. Zhuang, "Optimizing the Energy Delivery via V2G Systems Based on Stochastic Inventory Theory," IEEE Trans. Smart Grid., vol. 4, no. 4, pp. 22302243, 2013. [CrossRef] [Web of Science Times Cited 49] [SCOPUS Times Cited 57] [49] R.-E. Precup, S. Preitl, "Optimisation criteria in development of fuzzy controllers with dynamics," Engineering Applications of Artificial Intelligence, vol. 17, no. 6, pp. 661-674, 2004. [CrossRef] [Web of Science Times Cited 62] [SCOPUS Times Cited 79] [50] T. S. Li, C. T. Su, T. L.Chiang, "Applying robust multi-response quality engineering for parameter selection using a novel neuralgenetic algorithm," Computers in Industry, vol. 50, no. 1, pp. 113-122, 2003. [CrossRef] [Web of Science Times Cited 32] [SCOPUS Times Cited 43] [51] S. Vrkalovic, T.-A. Teban, I.-D. Borlea, "Stable Takagi-Sugeno fuzzy control designed by optimization," International Journal of Artificial Intelligence, vol. 15, no. 2, pp. 17-29, 2017. [52] R. D. Baruah, P. Angelov, "DEC: Dynamically Evolving Clustering and its application to structure identification of evolving fuzzy models," IEEE Trans. Cybern., vol. 44, no. 9, pp. 1619-1631, 2014. [CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 65] [53] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading: Addison-Wesley Publishing Company, p.62, 1989 [54] K. V. Price, "Differential evolution: a fast and simple numerical optimizer," in Proc. Fuzzy Inf. Process. Soc. Conf. North Am., Berkeley, CA, USA, 19-22 June 1996 pp. 524527. [CrossRef] [55] J. Kennedy, R. Eberhart, "Particle swarm optimization", in Proc. IEEE Int. Conf Neural Networks, Perth, Austuralia, 27 Nov.-1 Dec. 1995, pp. 19421948. [CrossRef] [Web of Science Times Cited 31441] [56] D. Karaboga, "An idea based on honey bee swarm for numerical optimization". Technical Report TR06, Erciyes University, Eng. Faculty, Computer Engineering Department, Oct. 2005. [Online] Available: Temporary on-line reference link removed - see the PDF document [57] R. Ranjan, D Das, "Simple and efficient computer algorithm to solve radial distribution networks," Electr Power Compon Syst., vol. 31 pp.95107, 2003 [CrossRef] [Web of Science Times Cited 50] [SCOPUS Times Cited 82] [58] GridLAB-D, [Online]. Available: http://www.gridlabd.org/ [59] D. P. Chassin, K. Schneider, C. Gerkensmeyer, "GridLABD: An open-source power systems modeling and simulation environment," in Proc. Transmission and Distribution Conference and Exposition, Chicago, USA, 21-24 April 2008, pp.1-5. [CrossRef] [SCOPUS Times Cited 325] [60] MATLAB, [Online]. Available: https://www.mathworks.com/products/matlab.html [61] J. C. Fuller, B. Vyakaranam, N. Prakash Kumar, S. M. Leistritz, G. B. Parker, "Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction," Technical Report-PNNL-21358 [Online] Available: Temporary on-line reference link removed - see the PDF document [62] Z. T. Taylor, K . Gowri, S. Katipamula, "GridLAB-D Technical Support Document: Residential End-Use Module Version 1.0," Technical Report-PNNL- 17694 [Online] Available: Temporary on-line reference link removed - see the PDF document [63] R. G. Pratt, C. C. Conner, E. E. Richman, K. G. Ritland, W. F. Sandusky, and M. E. Taylor, "Description of Electric Energy Use in Single Family Residences in the Pacific Northwest," DOE/BP 13795 21, Bonneville Power Administration, Portland, OR, 1989. [Online] Available: Temporary on-line reference link removed - see the PDF document [64] EN 50160, voltage characteristics of electricity supplied by public distribution systems, 1999. [65] S. Shao, M. Pipattanasomporn, and S. Rahman, "Grid Integration of Electric Vehicles and Demand Response With Customer Choice," IEEE Trans. Smart Grid., vol. 3, no. 1, pp. 543550, 2012. [CrossRef] [Web of Science Times Cited 267] [SCOPUS Times Cited 323] [66] FHA, "Summary of Travel Trends: 2009 National Household Travel Survey," p. 82, 2011. [67] J. D. Dogger, B. Roossien, and F. D. J. Nieuwenhout, "Characterization of Li-ion batteries for intelligent management of distributed grid connected storage," IEEE Trans. Energy Convers., vol. 26, no. 1, pp. 256 263, 2011. [CrossRef] [Web of Science Times Cited 120] [SCOPUS Times Cited 155] [68] E. Bompard, E. Carpaneto, G. Chicco, and R. Napoli, "Convergence of the backward / forward sweep method for the load-flow analysis of radial distribution systems," Int. J. of Elect. Power & Energy Syst., vol. 22, pp. 521530, 2000. [CrossRef] [Web of Science Times Cited 98] [SCOPUS Times Cited 117] [69] R.-E. Precup, R.-C. David, E. M. Petriu, M.-B. Radac, S. Preitl, J. Fodor, "Evolutionary optimization-based tuning of low-cost fuzzy controllers for servo systems," Knowledge-Based Systems, vol. 38, no. 9, pp. 74-84, 2013. [CrossRef] [Web of Science Times Cited 69] [SCOPUS Times Cited 77] [70] D. Zaharie, "Influence of crossover on the behavior of Differential Evolution Algorithms," Applied Soft Computing, vol. 9, no. 3, pp. 1126-1138, 2009. [CrossRef] [Web of Science Times Cited 226] [SCOPUS Times Cited 267] [71] A. W.Mohamed, H. Z. Sabry, M. Khorshid, "An alternative differential evolution algorithm for global optimization," Journal of Advanced Research, vol. 3, no. 2, pp. 149-165, 2012. [CrossRef] [Web of Science Times Cited 68] [SCOPUS Times Cited 83] [72] D. Karaboga B. Basturk, "On the performance of artificial bee colony (ABC) algorithm," Applied Soft Computing, vol. 8, no. 1, pp. 687697, 2008. [CrossRef] [Web of Science Times Cited 2476] [SCOPUS Times Cited 3244] Web of Science® Citations for all references: 43,320 TCR SCOPUS® Citations for all references: 16,329 TCR Web of Science® Average Citations per reference: 593 ACR SCOPUS® Average Citations per reference: 224 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 2024-04-18 22:18 in 345 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 ©2001-2024
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.
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.
