Open AccessA Hybrid Total Logistics Forecasting Method Combined with ARIMA and BPNN
Author(s) -
Jianjun Wang,
Yaqian Xing,
Shuo Zhang,
Yan Zhou,
Li Li,
Tiantian Nian
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1769/1/012051
Subject(s) - autoregressive integrated moving average , investment (military) , plan (archaeology) , china , operations research , business , five year plan , computer science , environmental economics , economics , time series , engineering , geography , archaeology , machine learning , politics , political science , law
In recent years, with the continuous improvement of China’s economic level, Chinese people’s living standards are also improving, so that the vigorous development of the e-commerce industry and the number of the total amount of social logistics have increased year by year, which has brought great impetus to the development of the logistics industry. Based on the background, it requires a scientific and reasonable forecasting result of the total amount of logistics for the logistics industry investment. This paper employs an ARIMA and BPNN combined method to forecast the total logistics situation during the “14th Five-Year Plan” period, the results show that the combination forecasting method can take into account the advantages of each single forecast model, and its forecast effect is more ideal.