Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/65694
Title: Forecasting GDP in ASIAN countries using relevant vector machines
Authors: Somsak Chanaim
Wilawan Srichaikul
Chongkolnee Rungruang
Songsak Sriboonchitta
Keywords: Mathematics
Issue Date: 1-Jan-2019
Abstract: © 2019 by the Mathematical Association of Thailand. All rights reserved. The GDP is very important for measure the economics growth in country, in this paper use the relevance vector machine(RVM) to predict the GDP in some ASIAN country (Thailand, Malaysia and Singapore) and compare with the autoregressive model (AR(p)). From the result show that RVM dominate the AP(p) model by measuring the error (MAE, MAPE, MSE and RMSE) from both training data and validation data.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85068484033&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/65694
ISSN: 16860209
Appears in Collections:CMUL: Journal Articles

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