Electrical load forecasting formulation by a fast neural network
| Autor: | Lopes, Mara Lúcia M. [UNESP], Minussi, Carlos R. [UNESP], Lotufo, Anna Diva P. [UNESP] |
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| Přispěvatelé: | Universidade Estadual Paulista (UNESP) |
| Jazyk: | angličtina |
| Rok vydání: | 2003 |
| Předmět: | |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| Popis: | Made available in DSpace on 2022-04-28T19:55:54Z (GMT). No. of bitstreams: 0 Previous issue date: 2003-03-01 The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective. Departamento de Engenharia Eletrica Universidade Estadual Paulista UNESP, Ilha Solteria, SP Departamento de Engenharia Eletrica Universidade Estadual Paulista UNESP, Ilha Solteria, SP |
| Databáze: | OpenAIRE |
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