Abstract
In order to improve the accuracy of prediction model for labor productivity in regional economic growth in China, a prediction method for labor productivity in regional economic growth in China based on analysis model of neural network of principal components is proposed. At first, principal component analysis method is used to simplify multiple index parameters describing characteristics of labor productivity samples of regional economic growth which may have certain correlation into several aggregative indexes; then, BP neural network algorithm is introduced to construct prediction model for labor productivity in regional economic growth in China; at last, the performance advantage of this algorithm is verified through simulation experiment.
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