Electrical load forecasting in disaggregated levels using Fuzzy ARTMAP artificial neural network and noise removal by singular spectrum analysis
| Autor: | Anna Diva P. Lotufo, E. M. Carreno, L. A. Teixeira, M. R. Müller, G. Gaio |
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| Přispěvatelé: | Universidade Estadual Paulista (Unesp), Western Parana State University – UNIOESTE, Federal Latin-American Integration University |
| Rok vydání: | 2020 |
| Předmět: |
Electrical load
Artificial neural network Series (mathematics) Computer science business.industry General Chemical Engineering General Engineering General Physics and Astronomy Pattern recognition Fuzzy ARTMAP Fuzzy logic Power load Reduction (complexity) Noise General Earth and Planetary Sciences General Materials Science Artificial intelligence business Singular spectrum analysis Randomness Forecasting General Environmental Science |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| ISSN: | 2523-3971 2523-3963 |
| Popis: | Made available in DSpace on 2021-06-25T10:47:53Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-07-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Electrical load forecasting in disaggregated levels is a difficult task due to time series randomness, which leads to noise and consequently affects the quality of predictions. To mitigate this problem, noise removal using singular spectrum analysis (SSA) is used in this work in conjunction with a Fuzzy ARTMAP artificial neural network, presenting excellent results when compared with traditional methods like SARIMA. A reduction of almost 50% on the MAPE is achieved. The SSA method is preferable to other filtering methods because it has a low computational cost, depends on a small number of parameters, requires few data to present good results, and it does not cause delay into the denoised series. Electrical Engineering Department UNESP-FEIS Engineering and Exact Sciences Center - CECE Western Parana State University – UNIOESTE UNILA Federal Latin-American Integration University Electrical Engineering Department UNESP-FEIS |
| Databáze: | OpenAIRE |
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