Abstract
Water is the source of life, and the water quality is of great significance to human life. There are many factors affecting water quality, so the water quality prediction is difficult. Time series is a model that is often used for forecasting. ARIMA is a more mature model of time series models and is often used in actual forecasting work. In this paper, a web crawler is designed to obtain water quality monitoring data, and a large data set of water quality monitoring is constructed. After data cleaning, the ARIMA model is used to predict the total phosphorus index of water quality. The experimental results show that the ARIMA model has a good effect in predicting the total phosphorus index of water quality.
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Acknowledgments
This research was funded by the National Natural Science Foundation of China (No. 61304208), Scientific Research Fund of Hunan Province Education Department (18C0003), Research project on teaching reform in colleges and universities of Hunan Province Education Department (20190147), Changsha City Science and Technology Plan Program (K1501013-11), Hunan Normal University University-Industry Cooperation. This work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property, Universities of Hunan Province, Open project, grant number 20181901CRP04.
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Wu, J. et al. (2022). Prediction of the Total Phosphorus Index Based on ARIMA. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13339. Springer, Cham. https://doi.org/10.1007/978-3-031-06788-4_29
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DOI: https://doi.org/10.1007/978-3-031-06788-4_29
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