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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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2017-Jun-14
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.

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  1/2014 - 2

A Combined Methodology of Adaptive Neuro-Fuzzy Inference System and Genetic Algorithm for Short-term Energy Forecasting

KAMPOUROPOULOS, K. See more information about KAMPOUROPOULOS, K. on SCOPUS See more information about KAMPOUROPOULOS, K. on IEEExplore See more information about KAMPOUROPOULOS, K. on Web of Science, ANDRADE, F. See more information about  ANDRADE, F. on SCOPUS See more information about  ANDRADE, F. on SCOPUS See more information about ANDRADE, F. on Web of Science, GARCIA, A. See more information about  GARCIA, A. on SCOPUS See more information about  GARCIA, A. on SCOPUS See more information about GARCIA, A. on Web of Science, ROMERAL, L. See more information about ROMERAL, L. on SCOPUS See more information about ROMERAL, L. on SCOPUS See more information about ROMERAL, L. 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 (682 KB) | Citation | Downloads: 751 | Views: 3,047

Author keywords
adaptive neuro-fuzzy inference system, energy forecast, genetic algorithm, intelligent energy management systems

References keywords
energy(13), systems(9), load(7), neural(6), fuzzy(6), applications(6), term(5), short(5), optimization(5), network(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 9 - 14
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01002
Web of Science Accession Number: 000332062300002
SCOPUS ID: 84894611007

Abstract
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This document presents an energy forecast methodology using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithms (GA). The GA has been used for the selection of the training inputs of the ANFIS in order to minimize the training result error. The presented algorithm has been installed and it is being operating in an automotive manufacturing plant. It periodically communicates with the plant to obtain new information and update the database in order to improve its training results. Finally the obtained results of the algorithm are used in order to provide a short-term load forecasting for the different modeled consumption processes.


References | Cited By

Cited-By ISI Web of Science

Web of Science® Times Cited: 9 [View]
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Cited-By CrossRef

SCOPUS® Times Cited: 15
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Cited-By CrossRef

[1] Integrated Forecasting Using the Discrete Wavelet Theory and Artificial Intelligence Techniques to Reduce the Bullwhip Effect in a Supply Chain, Singh, Lakhwinder Pal, Challa, Ravi Teja, Global Journal of Flexible Systems Management, ISSN 0972-2696, Issue 2, Volume 17, 2016.
Digital Object Identifier: 10.1007/s40171-015-0115-z
[CrossRef]

[2] Industrial Time Series Modelling by Means of the Neo-Fuzzy Neuron, Zurita, Daniel, Delgado, Miguel, Carino, Jesus A., Ortega, Juan A., Clerc, Guy, IEEE Access, ISSN 2169-3536, Issue , 2016.
Digital Object Identifier: 10.1109/ACCESS.2016.2611649
[CrossRef]

[3] A Multi-objective PMU Placement Method Considering Observability and Measurement Redundancy using ABC Algorithm, KULANTHAISAMY, A., VAIRAMANI, R., KARUNAMURTHI, N. K., KOODALSAMY, C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 14, 2014.
Digital Object Identifier: 10.4316/AECE.2014.02020
[CrossRef] [Full text]

[4] Estimation of DSI log parameters from conventional well log data using a hybrid particle swarm optimization–adaptive neuro-fuzzy inference system, Zahmatkesh, Iman, Soleimani, Bahman, Kadkhodaie, Ali, Golalzadeh, Alireza, Abdollahi, AliAkbar- Moussavi, Journal of Petroleum Science and Engineering, ISSN 0920-4105, Issue , 2017.
Digital Object Identifier: 10.1016/j.petrol.2017.08.002
[CrossRef]

[5] A Novel Evolutionary Genetic Optimization-Based Adaptive Neuro-Fuzzy Inference System and Geographical Information Systems Predict and Map Soil Organic Carbon Stocks Across an Afromontane Landscape, WERE, Kennedy O., TIEN BUI, Dieu, DICK, Øystein Bjarne, SINGH, Bal Ram, Pedosphere, ISSN 1002-0160, Issue 5, Volume 27, 2017.
Digital Object Identifier: 10.1016/S1002-0160(17)60461-2
[CrossRef]

[6] Prediction of lung nicotine concentration based on novel GA-ANFIS system approach, Begic Fazlic, Lejla, Avdagic, Aja, 2015 XXV International Conference on Information, Communication and Automation Technologies (ICAT), ISBN 978-1-4673-8146-8, 2015.
Digital Object Identifier: 10.1109/ICAT.2015.7340520
[CrossRef]

[7] Optimization of a combined cool, heat and power plant based on genetic algorithms and specialized software, Hopulele, Eugen, Gavrilas, Mihai, 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-4799-5849-8, 2014.
Digital Object Identifier: 10.1109/ICEPE.2014.6970065
[CrossRef]

[8] Smart multi-model approach based on adaptive Neuro-Fuzzy Inference Systems and Genetic Algorithms, Sala, Enric, Kampouropoulos, Konstantinos, Giacometto, Francisco, Romeral, Luis, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, ISBN 978-1-4799-4032-5, 2014.
Digital Object Identifier: 10.1109/IECON.2014.7048513
[CrossRef]

[9] Multi-carrier optimal power flow of energy hubs by means of ANFIS and SQP, Kampouropoulos, Konstantinos, Andrade, Fabio, Sala, Enric, Espinosa, Antonio Garcia, Romeral, Luis, IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, ISBN 978-1-5090-3474-1, 2016.
Digital Object Identifier: 10.1109/IECON.2016.7793570
[CrossRef]

[10] GA-ANFIS expert system prototype for detection of tar content in the manufacturing process, Fazlic, Lejla Begic, Avdagic, Zikrija, Besic, Ingmar, 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), ISBN 978-9-5323-3082-3, 2015.
Digital Object Identifier: 10.1109/MIPRO.2015.7160457
[CrossRef]

[11] Optimal control of energy hub systems by use of SQP algorithm and energy prediction, Kampouropoulos, Konstantinos, Andrade, Fabio, Sala, Enric, Romeral, Luis, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, ISBN 978-1-4799-4032-5, 2014.
Digital Object Identifier: 10.1109/IECON.2014.7048503
[CrossRef]

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


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