A time series forecasting system based on ARIMA for industrial big data

Yang Du

doi:10.1117/12.2641141

2 December 2022 A time series forecasting system based on ARIMA for industrial big data

Yang Du

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 1228805 (2022) https://doi.org/10.1117/12.2641141
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

Time series analysis has played an important role in human production practice and scientific research. And the ARIMA model is a model often used when researching and forecasting time series. In this paper, we construct multiple groups of ARIMA models in the experiment and conduct white noise test and parameter significance test. The results show that the ARIMA (1,1,1) model is relatively optimal. Then applied the ARIMA model to describe and predict the PMI index of China's manufacturing industry, revealing the underlying economic laws. Judging from the forecast results of the manufacturing PMI index in year 2021: The ARIMA model can be used for short-term forecasting of the PMI index, and the model has a high degree of fit. The forecast model has certain application value. This model can bring better prediction and get more accurate future estimation in the field of robotics, automation and intelligent control.

Citation Download Citation

Yang Du "A time series forecasting system based on ARIMA for industrial big data", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 1228805 (2 December 2022); https://doi.org/10.1117/12.2641141

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