MATEC Web Conf.
Volume 309, 20202019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|Number of page(s)||8|
|Section||Modelling and Simulation|
|Published online||04 March 2020|
A time prediction model for residents consumption level based on ARIMA and PCA
School of Information Engineering, Dalian Ocean University, 116023 Dalian, China
* Corresponding author: firstname.lastname@example.org
It is necessary but difficult to make a large number of observations on multiple variables reflecting the residents consumption level and collect a large amount of data for analysis to search for the rules. In this paper, a time prediction model for residents consumption level based on ARIMA and principal component analysis is proposed to solve this problem. Principal component analysis is firstly used to effectively reduce the number of indicators reflecting the residents consumption level. Combined with the ARIMA model, the residents consumption level is predicted. The results reflect the trend of residents consumption level towards the need for enjoyment and development materials on the basis of obtaining basic survival data.
Key words: Resident consumption level / Principal component analysis / Data dimension reduction / ARIMA model
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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