Water quality prediction method and device, electronic equipment and storage medium

Abstract

The invention discloses a water quality prediction method and device, electronic equipment and a computer readable storage medium. The water quality prediction method comprises the following steps: establishing a water quality prediction model based on a neural network model, wherein the neural network model is one or a combination of more of a long-short term memory neural network model (LSTM), a recurrent neural network model (RNN), a back propagation neural network model (BP) and a convolutional neural network model (CNN); training the water quality prediction model based on historical water quality monitoring target data and potential characteristic factor data; and predicting the water quality based on the water quality prediction model. According to the technical scheme provided by the invention, the influence of the potential characteristic factor data related to the water quality monitoring target data is fully considered, and the data is flexibly applied, so that the characteristics which can be provided by the data are reasonably found, and the simulation accuracy of the model is improved.

Description

technical field [0001] The invention relates to the technical field of environmental protection, in particular to a water quality prediction method, device, electronic equipment and storage medium. Background technique [0002] Most of the existing river and lake water quality prediction methods use single-factor historical data as training samples for curve fitting. This method has high practicability in industries with relatively mature data such as finance, but in water quality prediction based on automatic monitoring stations, due to the large number of direct and indirect factors affecting water quality and the amount of existing data is not enough to find out Stable rules and single-factor prediction methods often cannot meet the requirements of prediction accuracy. At the same time, due to the uneven quality of historical water quality monitoring data at this stage, frequent downtime of monitoring instruments, and many outliers in monitoring results, it is easy to af...

AI Technical Summary

Problems solved by technology

The invention patent application pointed out the quality problem of the monitoring data, but in the process of data preprocessing, only the vacant data was deleted, which would lead to the discontinuity of the data on the time axis, which could not reflect the law of data changes well

At the same time, in the selection process of water quality index parameters, the patent proposes to select indicators based on water environment experience, but does not combine the indicators, and cannot play the role of related indicators well

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