River network water quality monitoring method and device and readable storage medium
A technology for water quality and river network, applied in the field of monitoring, which can solve problems such as not being forward-looking and unable to model data.
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Embodiment 1
[0056] like figure 1 As shown, the present embodiment provides a method for monitoring the water quality of a river network, the river network includes a plurality of rivers, and the monitoring method includes the following steps:
[0057] Step S102, obtaining the first data of all river monitoring sections, the first data includes the first flow rate, the first water level, the salinity, and the first pollutant concentration;
[0058] Step S104, obtaining the second data of the sewage outlets of enterprises in the river network, the second data includes the second flow rate and the second pollutant concentration;
[0059] Step S106, obtaining meteorological data of the river network, the meteorological data includes temperature, wind speed, wind direction, and rainfall;
[0060] Step S108, based on the first data, using the neural network model to obtain the predicted flow and predicted water level of all river monitoring sections;
[0061] Step S110, based on the first dat...
Embodiment 2
[0066] like figure 2 As shown, the present embodiment provides a method for monitoring the water quality of the river network. In addition to the technical features of the above-mentioned embodiments, the present embodiment further includes the following technical features:
[0067] Before obtaining the first data of all river monitoring sections, the following steps are also included:
[0068] Step S202, obtaining the historical data of each river monitoring section in the first time period, the historical data includes the third flow and the second water level;
[0069] Step S204, cleaning the historical data, and normalizing the cleaned historical data;
[0070] Step S206, for the historical data after the normalization process, the data at multiple consecutive moments are used as input, and the data at the next moment is used as output to obtain an input data set and an output data set;
[0071] Step S208, splitting the input data set and the output data set into traini...
Embodiment 3
[0081] like image 3 As shown, the present embodiment provides a method for monitoring the water quality of the river network. In addition to the technical features of the above-mentioned embodiments, the present embodiment further includes the following technical features:
[0082] Based on the first data, the neural network model is used to obtain the predicted discharge and predicted water level of all river monitoring sections, which specifically includes the following steps:
[0083] Step S302, obtain the first flow rate and the first water level of each river monitoring section at the current moment and previous consecutive times as input, input it into the trained deep learning neural network model of the river, and obtain the predicted flow rate and the first water level of each river monitoring section Forecast water levels.
[0084] In this embodiment, for the trained deep learning neural network model of the river, the first flow rate and the first water level at t...
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