Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.315
According to the historical data of ×× Factory, we use ARIMA time series to model how to predict the demand for spare parts of ×× Factory. The forecast model test results show that the model can better predict, with high accuracy. On this basis, this article predicts the demand for spare parts of next year.
ARIMA, Time Series, Demand forecast
Ren Jiafu, Zhang Fang, "The Forecasting Models for Spare Parts Based on ARMA", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 499-503, doi:10.1109/CSIE.2009.315