Abstract
FS-BP model was used to try to predict precipitation. The last six years’ precipitation were selected as input variable and the next year’s precipitation as output variable. The results show that the mean relative error of the prediction is 2.92%. T-test and regression analysis indicates that the predicted value differs just slightly from the observed value and their correlation coefficient was 0.9901.The FS-BP model is quite higher than BP model in accuracy and stability, and serves as useful tool in further research on prediction of precipitation.
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© 2011 Springer-Verlag Berlin Heidelberg
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Yin, GH., Gu, J., Zhang, FS., Shen, YJ., Liu, Zx. (2011). Prediction of Precipitation Based on Artificial Neural Networks by Free Search. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23756-0_61
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DOI: https://doi.org/10.1007/978-3-642-23756-0_61
Publisher Name: Springer, Berlin, Heidelberg
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