ARIMA-GRU water quality prediction method based on wavelet decomposition

Yanbing Wang; Fang Lv

doi:10.1117/12.2674722

2 May 2023 ARIMA-GRU water quality prediction method based on wavelet decomposition

Yanbing Wang, Fang Lv

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 126420I (2023) https://doi.org/10.1117/12.2674722
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

With the continuous progress of society and economy, the management of water resources and the prevention and control of sewage are becoming more and more important. Due to the complex structure of the mechanistic prediction model and the huge amount of computation, the universality is weak, and it is not easy to generalize. In order to improve the prediction accuracy of water quality index data, this paper proposes an ARIMA-GRU water quality prediction model based on wavelet decomposition. The model divides the water quality index data into high-frequency components and low-frequency components through wavelet decomposition and coefficient reconstruction, which are respectively input into the differential autoregressive moving average model (ARIMA) and the gated recurrent neural network (GRU), and then each model is used. The predicted values are combined to obtain the final prediction result. Compared with a single prediction model, the water quality prediction model has better accuracy and higher coincidence with the real value, and has practical application value.

Citation Download Citation

Yanbing Wang and Fang Lv "ARIMA-GRU water quality prediction method based on wavelet decomposition", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 126420I (2 May 2023); https://doi.org/10.1117/12.2674722

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