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dc.contributor.authorSomsak Chanaimen_US
dc.contributor.authorWilawan Srichaikulen_US
dc.contributor.authorChongkolnee Rungruangen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.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.en_US
dc.titleForecasting GDP in ASIAN countries using relevant vector machinesen_US
article.title.sourcetitleThai Journal of Mathematicsen_US
article.volume17en_US of Songkla Universityen_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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