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• W2001086848 abstract "Forecasting in several areas such as stock price, electricity power consumption, tourist arrival rates or capacity planning allows us to give decisions for future events. The rising up or falling down of the values can support researchers, economists or investors while giving their important decisions. This study aims to forecast the directional movements of electricity load demands and evaluates the performance on 3 load datasets. In experimental results, the proposed Empirical Mode Decomposition (EMD) and Support Vector Regression (SVR) based hybrid method is compared with single SVR. It is observed that the proposed EMD-SVR method outperforms the single SVR performance on direction measurements including Direction Accuracy, Correct Up and Correct Down trends." @default.
• W2001086848 created "2016-06-24" @default.
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• W2001086848 date "2014-05-01" @default.
• W2001086848 modified "2023-09-23" @default.
• W2001086848 title "A hybrid method for time series prediction using EMD and SVR" @default.
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• W2001086848 doi "https://doi.org/10.1109/isccsp.2014.6877938" @default.
• W2001086848 hasPublicationYear "2014" @default.
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