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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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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
 
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Download PDF pdficon (682 KB) | Citation | Downloads: 1,278 | Views: 5,319

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

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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
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[2] New modified CHB multilevel inverter topology with elimination of lower and higher order harmonics, Chabni, Fayçal, Taleb, Rachid, Lakhedar, Abdelhak, Bounadja, Mohammed, Automatika, ISSN 0005-1144, Issue 1, Volume 59, 2018.
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[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.
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[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.
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[6] INVERSE NEURO-FUZZY MODEL BASED CONTROLLER DESIGN FOR A PH NEUTRALIZATION PROCESS, AKCA, Talha Burak, ULU, Cenk, OBUT, Salih, Journal of Scientific Reports-A, ISSN 2687-6167, Volume , 2023.
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[9] Using Hybrid Wavelet Approach and Neural Network Algorithm to Forecast Distribution Feeders, Bagheri, Mehdi, Zadehbagheri, Mahmoud, Kiani, Mohammad Javad, Zamani, Iman, Nejatian, Samad, Journal of Electrical Engineering & Technology, ISSN 1975-0102, Issue 3, Volume 18, 2023.
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[10] Fuzzy Logic for Solving the Water-Energy Management Problem in Standalone Water Desalination Systems, Ben Ali, Ines, Turki, Mehdi, Belhadj, Jamel, Roboam, Xavier, International Journal of Fuzzy System Applications, ISSN 2156-177X, Issue 1, Volume 12, 2023.
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[11] 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.
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[12] 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.
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[13] 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.
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[14] 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.
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[15] 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.
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[16] 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.
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