An ERBF Network Prediction of Taiwan’s Crude Birth Rate Taking Economic Growth Rate and National Income Indices as Input Variables

Yi Ti Tung; Tzu Yi Pai

doi:10.4028/www.scientific.net/AMR.1044-1045.1721

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1044-1045An ERBF Network Prediction of Taiwan’s Crude Birth...

An ERBF Network Prediction of Taiwan’s Crude Birth Rate Taking Economic Growth Rate and National Income Indices as Input Variables

Abstract:

In this study, exact radial basis function (ERBF) network was used to predict Taiwan’s crude birth rate (CBR), taking the economic growth rate (EGR) and national income indices (NII) as input variables. To establish the ERBF network model, the EGR and NII were taken as the input variables, and the CBR was taken as the output variable. The results indicated that the minimum mean absolute percentage error (MAPE), mean squared error (MSE), root mean squared error (RMSE), and maximum correlation coefficient (R) was 0.00 %, 0.00, 0.00, and 1.00, respectively when training. Those for testing were 52.41 %, 27.88, 5.28, and 0.00, respectively. According to the results, ERBF network could predict CBR by taking the EGR and NII as input variables.

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Periodical:

Advanced Materials Research (Volumes 1044-1045)

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1721-1724

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https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.1721

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Online since:

October 2014

Authors:

Yi Ti Tung, Tzu Yi Pai

Keywords:

Crude Birth Rate, Economic Growth Rate, Exact Radial Basis Function (ERBF) Network, GDP, GNP, National Income Indices

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