Analysis and Forecast of Total Investment in Environmental Pollution Treatment in China Based on ARIMA Model
- DOI
- 10.2991/978-94-6463-198-2_135How to use a DOI?
- Keywords
- Environmental pollution management; time series; ARIMA model
- Abstract
In this paper, by selecting the annual data of total investment in environmental pollution control in China from 2002 to 2021 and using R language to process and test the data, an optimal ARIMA (1,2,1) model is established, which is used to make the total investment in environmental pollution control in China for the next five years from 2022 to 2026. The model is used to forecast the total investment in environmental pollution control in China for the next five years 2022–2026. According to the model, the total investment in environmental pollution control in the next five years is predicted to be 1,029.472 billion yuan, 10,132.279 billion yuan, 1,044.827 billion yuan, 1,052.752 billion yuan, and 1,072.366 billion yuan, indicating an overall upward trend from 2022 to 2026, but more slowly. This reflects that China’s environmental problems are still serious, and the country should pay more attention to environmental and ecological problems, and finally put forward reasonable proposed measures.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yan Zhang AU - Qian Ma AU - Lijuan Du PY - 2023 DA - 2023/08/10 TI - Analysis and Forecast of Total Investment in Environmental Pollution Treatment in China Based on ARIMA Model BT - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) PB - Atlantis Press SP - 1296 EP - 1307 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-198-2_135 DO - 10.2991/978-94-6463-198-2_135 ID - Zhang2023 ER -