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APPLICATION OF EMPIRICAL MODE DECOMPOSITION WITH WAVELETS SUPPORT VECTOR MACHINE IN TIME SERIES DATA

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dc.contributor.author A. RAFIDAH
dc.contributor.author ANI SHABRI
dc.contributor.author ERNIE MAZUIN
dc.contributor.author (UniKL MITEC)
dc.date.accessioned 2020-01-12T02:03:16Z
dc.date.available 2020-01-12T02:03:16Z
dc.date.issued 2020-01-12
dc.identifier.uri http://ir.unikl.edu.my/jspui/handle/123456789/23631
dc.description.abstract This paper mainly discussed on the forecast of Thailand tourist visiting Malaysia. This paper proposed a three-stage technique in which the empirical mode decomposition (EMD) is combined with wavelet methods and support vector machine model. We used the proposed technique, EMD_WSVM to forecast two ASEAN country tourism time series. Detail experiments are conducted for the proposed method, in which there is a comparison between the EMD_WSVM, WSVM and SVM methods. The proposed EMD_WSVM model is determined to be dominant to the other methods in predicting the number of tourist arrivals. en_US
dc.subject Forecasting en_US
dc.subject tourist arrivals en_US
dc.subject SVM model en_US
dc.subject WSVM model en_US
dc.subject EMD_WSVM model en_US
dc.title APPLICATION OF EMPIRICAL MODE DECOMPOSITION WITH WAVELETS SUPPORT VECTOR MACHINE IN TIME SERIES DATA en_US
dc.conference.name INTERNATIONAL RESEARCH CONFERENCE AND INNOVATION EXHIBITION en_US
dc.conference.year 2019 en_US


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