Water pollution prediction method and device and electronic device
A prediction method and water pollution technology, applied in the field of data processing, can solve the problem of not considering the impact, and achieve the effect of improving the accuracy
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Embodiment 1
[0058] The embodiment of the present application provides a water pollution prediction method, such as figure 1 As shown, the method includes: step S101 to step S105.
[0059] Step S101. Obtain the data to be measured at the first station and the data to be measured at at least one second station within a predetermined area corresponding to the first station. The data to be measured include time-series data of water quality and time-series information of hydrology.
[0060] In the embodiment of the present application, the time-series data of water quality is used to represent the water quality status of the current water area. In practical application, different values can be set for the water quality data, and different levels can be set for different value intervals. For example, if the value corresponding to the PH of the water quality is 10, the corresponding level is VI level and cannot be drunk.
[0061] In the embodiment of the present application, the hydrological ...
Embodiment 2
[0095] The embodiment of the present application provides a water pollution prediction device, such as image 3 As shown, the water pollution prediction device 30 may include: a data acquisition module 301, an impact determination module 302, a predicted value acquisition module 303, and a prediction processing module 304, wherein,
[0096] The data acquisition module 301 is used to acquire the data to be measured of the first site and the data to be measured of at least one second site in the predetermined area corresponding to the first site, the data to be measured includes water quality time-series data and hydrological time-series information;
[0097] The impact determination module 302 is configured to input the data to be tested obtained from the first site into the preset first convolutional neural network model for feature extraction, and use the attention mechanism attention of the first convolutional neural network model for processing, to obtain The first impact p...
Embodiment 3
[0114] The embodiment of the present application provides an electronic device, such as Figure 5 as shown, Figure 5 The electronic device 400 shown includes: a processor 4001 and a memory 4003 . Wherein, the processor 4001 is connected to the memory 4003 , such as through a bus 4002 . Further, the electronic device 400 may further include a transceiver 4004 . It should be noted that, in practical applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 400 does not limit the embodiment of the present application.
[0115] The processor 4001 may be a CPU, a general purpose processor, DSP, ASIC, FPGA or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute the various illustrative logical blocks, modules and circuits described in connection with the present disclosure. The processor 4001 may also be a combination that implements computing functions,...
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Abstract
Description
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Application Information
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