| dc.contributor | Universidade Estadual Paulista (UNESP) | |
| dc.creator | Lopes, MLM | |
| dc.creator | Minussi, C. R. | |
| dc.creator | Lotufo, ADP | |
| dc.date | 2014-05-20T13:29:02Z | |
| dc.date | 2016-10-25T16:48:30Z | |
| dc.date | 2014-05-20T13:29:02Z | |
| dc.date | 2016-10-25T16:48:30Z | |
| dc.date | 2005-01-01 | |
| dc.date.accessioned | 2017-04-05T20:12:46Z | |
| dc.date.available | 2017-04-05T20:12:46Z | |
| dc.identifier | Applied Soft Computing. Amsterdam: Elsevier B.V., v. 5, n. 2, p. 235-244, 2005. | |
| dc.identifier | 1568-4946 | |
| dc.identifier | http://hdl.handle.net/11449/9740 | |
| dc.identifier | http://acervodigital.unesp.br/handle/11449/9740 | |
| dc.identifier | 10.1016/j.asoc.2004.07.003 | |
| dc.identifier | WOS:000227208700008 | |
| dc.identifier | http://dx.doi.org/10.1016/j.asoc.2004.07.003 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/857802 | |
| dc.description | This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved. | |
| dc.language | eng | |
| dc.publisher | Elsevier B.V. | |
| dc.relation | Applied Soft Computing | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | adaptive resonance theory | |
| dc.subject | electric load forecasting | |
| dc.subject | electric power systems | |
| dc.subject | neural networks | |
| dc.subject | fuzzy logic | |
| dc.subject | fuzzy ART&ARTMAP neural network | |
| dc.title | Electric load forecasting using a fuzzy ART&ARTMAP neural network | |
| dc.type | Otro | |
