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

Autor
Kampouropoulos, K.; Andrade, F.; Garcia, A.; Romeral, L.
Tipus d'activitat
Article en revista
Revista
Advances in Electrical and Computer Engineering
Data de publicació
2014-02-01
Volum
14
Número
1
Pàgina inicial
9
Pàgina final
14
DOI
https://doi.org/10.4316/AECE.2014.01002 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/22425 Obrir en finestra nova
Resum
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....
Citació
Kampouropoulos, K. [et al.]. A combined methodology of adaptive neuro-fuzzy inference system and genetic algorithm for short-term energy forecasting. "Advances in Electrical and Computer Engineering", Febrer 2014, vol. 14, núm. 1, p. 9-14.
Paraules clau
NETWORK, adaptive neuro-fuzzy inference system, energy forecast, genetic algorithm, intelligent energy management systems
Grup de recerca
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC

Participants

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