Abstract
BP neural network and multiple linear regression model can be used for multi-factor analysis and forecasting, but the data of the multiple linear regression required to meet independence, normality and other conditions, while the data of the BP neural network do not need to. This article uses the same set of data to established BP neural network model and multiple linear regression model, then compare the ability of fitting and forecasting of the two kinds of models finding that BP neural network has a strong fitting ability and a stable ability of prediction, which can be further used and promoted in the anglicizing and forecasting of the continuous data factors.
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Wang, G., Wu, J., Yin, S., Yu, L., Wang, J. (2010). Comparison between BP Neural Network and Multiple Linear Regression Method. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Lecture Notes in Computer Science, vol 6377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16167-4_47
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DOI: https://doi.org/10.1007/978-3-642-16167-4_47
Publisher Name: Springer, Berlin, Heidelberg
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