Verifying The Use Of Evolving Fuzzy Systems For Multi-step Ahead Daily Inflow Forecasting

dc.creatorLuna I.
dc.creatorSoares S.
dc.creatorLopes J.E.G.
dc.creatorBallini R.
dc.date2009
dc.date2015-06-26T13:34:36Z
dc.date2015-11-26T14:43:56Z
dc.date2015-06-26T13:34:36Z
dc.date2015-11-26T14:43:56Z
dc.date.accessioned2018-03-28T21:52:24Z
dc.date.available2018-03-28T21:52:24Z
dc.identifier9781424450985
dc.identifier2009 15th International Conference On Intelligent System Applications To Power Systems, Isap '09. , v. , n. , p. - , 2009.
dc.identifier
dc.identifier10.1109/ISAP.2009.5352814
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-76549132747&partnerID=40&md5=422993c9d102504cebbdbe4d1edb0514
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/92013
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/92013
dc.identifier2-s2.0-76549132747
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1251904
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionThis study presents a prediction system based on evolving fuzzy models and a bottom-up approach for daily streamflow forecasting. Prediction models are based on adaptive Takagi-Sugeno fuzzy inference systems. These models make use of a sequential learning approach for updating their own structure and parameters over time according to changes or variations identified in the series, whereas rainfall and runoff information is processed at each time instant. Models are adjusted following a bottom-up approach, which consists of dividing the global problem into sub-problems, and each sub-problem is resolved separately. Final estimate is given by the aggregation of the parts. The proposed approach is compared to the Soil Moisture Accounting Procedure (SMAP), a hydrological model used by various hydroelectric companies of the Brazilian electrical sector. Simulation studies indicate that the evolving fuzzy system presents an adequate performance, leading to a promising alternative for daily streamflow forecasting. Indeed, results are improved when predictors are combined, primarily for a multistep ahead prediction task. © 2009 IEEE.
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dc.descriptionCNPq,CAPES,Araucaria FAPEMIG - Brazilian res. funding agencies Found.,COPEL,Itaipu Power Plant
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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dc.languageen
dc.publisher
dc.relation2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09
dc.rightsfechado
dc.sourceScopus
dc.titleVerifying The Use Of Evolving Fuzzy Systems For Multi-step Ahead Daily Inflow Forecasting
dc.typeActas de congresos


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