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A combined methodology of adaptive neuro-fuzzy inference system and genetic algorithm for short-term energy forecasting
dc.contributor.author | Kampouropoulos, Konstantinos |
dc.contributor.author | Andrade Rengifo, Fabio |
dc.contributor.author | García Espinosa, Antonio |
dc.contributor.author | Romeral Martínez, José Luis |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica |
dc.date.accessioned | 2014-03-28T11:53:52Z |
dc.date.available | 2014-03-28T11:53:52Z |
dc.date.created | 2014-02 |
dc.date.issued | 2014-02 |
dc.identifier.citation | 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. |
dc.identifier.issn | 1582-7445 |
dc.identifier.uri | http://hdl.handle.net/2117/22425 |
dc.description.abstract | 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 shortterm load forecasting for the different modeled consumption processes. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Enginyeria electrònica |
dc.subject.lcsh | Genetic algorithms |
dc.subject.other | Adaptive neuro-fuzzy inference system |
dc.subject.other | Energy forecast |
dc.subject.other | Genetic algorithm |
dc.subject.other | Intelligent energy management systems |
dc.title | A combined methodology of adaptive neuro-fuzzy inference system and genetic algorithm for short-term energy forecasting |
dc.type | Article |
dc.subject.lemac | Programació genètica (Informàtica) |
dc.subject.lemac | Energia -- Gestió |
dc.contributor.group | Universitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group |
dc.identifier.doi | 10.4316/AECE.2014.01002 |
dc.rights.access | Open Access |
local.identifier.drac | 13848654 |
dc.description.version | Postprint (published version) |
local.citation.author | Kampouropoulos, K.; Andrade, F.; Garcia, A.; Romeral, J. |
local.citation.publicationName | Advances in Electrical and Computer Engineering |
local.citation.volume | 14 |
local.citation.number | 1 |
local.citation.startingPage | 9 |
local.citation.endingPage | 14 |
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