River sudden water pollution early warning traceability method and system, terminal and medium
A technology for water pollution and pollution sources, which is applied in the direction of testing organic pollutants in water, general water supply saving, and testing water, etc. It can solve the problems such as difficulty in satisfying the calculation conditions of the traceability model, large amount of calculation, and insufficient accuracy of traceability results, etc., so as to improve the alarm Accuracy and timeliness, improving search accuracy and improving decision-making efficiency
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Embodiment 1
[0065] Embodiment 1: A method for early warning and traceability of river sudden water pollution, such as figure 1 shown, including the following steps:
[0066] S101: Obtain online monitoring data and historical monitoring data of routine indicators of water quality.
[0067] S102: Start an abnormal algorithm for the received online monitoring data to analyze and predict water quality, and perform early warning and forecast for detected abnormal instantaneous water quality events. The early warning and forecasting of abnormal instantaneous water quality events is as follows: using spectral analysis data to drive the model to predict the baseline error distribution and threshold of the corrected model to detect abnormal water quality, including:
[0068] In the first stage, the power spectral density in the Fourier transform is used to identify the periodic changes and anomalies of historical monitoring data. The first stage is specifically:
[0069] The formula for calcula...
Embodiment 2
[0100] Embodiment 2: A kind of early warning and traceability system of river sudden water pollution, such as figure 2 As shown, it includes a host system, an information collection device, an input device, and an output display device.
[0101] The host system is networked with the GIS geographic information system, and the host system includes a first processor and a second processor. The first processor, embedded with ARIMA model, spectral analysis, Facebook Prophet model and wavelet ANN model, is used for real-time analysis and prediction of the received water quality online monitoring data, and forecast and early warning of detected abnormal instantaneous water quality events. The second processor is embedded with an active item model and an optimal search and tracking model, and is used to receive various types of information collected by input devices or information collection devices, and continuously optimize and adjust the mosaic model according to the received vari...
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