


Volume 16 No 6 (2018)
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A New BP Neural Network Model for the Prediction Problem of Equally Spaced Time Sequences and Its Application
Mengxia Li Ruiquan Liao , Yong Dong
Abstract
For the prediction of equally spaced time sequences, this paper proposes a new construction method for training
datasets based on the method which is used to determine parameters of the ARIMA model and builds a new BP
neural network predictive model. For the actual data of annual power consumption in China from 1980 to 2016,
data from 1980 to 2013 are chosen for this paper to construct the training dataset, and then the model proposed in
this paper and the standard BP model are used to predict the power consumption from 2014 to 2016. Finally, after
comparing the results obtained from the model proposed in this paper and the standard BP model, the prediction
accuracy obtained by the model used here is found to be no more than 2%
Keywords
BP Neural Network, Time window translation, ARIMA model
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