Application of RBF Neural Network Model on Forecasting Tourists Quantity in Hainan Province - Advanced Research on Computer Education, Simulation and Modeling - page 311

As can be seen from Table 4, after a slow growth phase from 2009 to 2015, tourists
quantity in Hainan Province will be gradually stabilized, in between 34 million to 35
million.
4 Conclusion
This paper has presented a tourists prediction method based on RBF neural net-
work.Through RBF neural network adaptive, self-organization and self-learning func-
tion, making tourists quantity every 5 years as the RBF neural network's input, we can
predict tourists quantity in the sixth year. After MATLAB training, forecasting,
simulation, this method achieves a good prediction effect. The use of this method
provides a new way of thinking for simulating and predicting tourists quantity in
Hainan province, provides a reference for the construction of Hainan International
Tourism Island.
Acknowledgements
This work is partly supported by Hainan University Graduate Education Reform
Project (yjg0117), and by Natural Science Foundation of Hainan Province (60894), and
by Education Department of Hainan Province project (Hjkj2009-03).
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