Orientador: Anna Diva Plasencia Lotufo / Resumo: This work analysis load data from desegregated levels that presented difficulties to load forecasting with several methods due to variation in electrical energy consumption. The application proposed in this work is short-term load forecasting to a university building by GRNN (General Regression Neural Network) considering the bottom up approach and using a moving average filter to deal with the missing or wrong data. It is presented the system that provides the data as well as the methods used for pre-processing and realize the forecasting. The results are evaluated by MAPE (Mean Absolute Perceptual Error) and are considered good when compared with other methods. / Mestre
| Identifer | oai:union.ndltd.org:UNESP/oai:www.athena.biblioteca.unesp.br:UEP01-000882396 |
| Date | January 2017 |
| Creators | Carvalho, Monara Pereira da Rosa |
| Contributors | Universidade Estadual Paulista "Júlio de Mesquita Filho" Faculdade de Engenharia (Campus de Ilha Solteira). |
| Publisher | Ilha Solteira, |
| Source Sets | Universidade Estadual Paulista |
| Language | Portuguese |
| Detected Language | English |
| Type | text |
| Format | f. |
| Relation | Sistema requerido: Adobe Acrobat Reader |
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