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Watershed pollution traceability prediction method and device based on artificial intelligence

A technology of pollution traceability and artificial intelligence, applied in the field of artificial intelligence-based watershed pollution traceability and prediction, can solve the problems of comprehensive identification of massive information and analysis of point source pollution, rapid and accurate identification, etc.

Inactive Publication Date: 2022-02-18
BEIJING NORMAL UNIVERSITY
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Problems solved by technology

[0006] Aiming at the problem that the existing technology cannot satisfy the comprehensive identification and analysis of massive information and the rapid and accurate identification of point source pollution, the present invention proposes an artificial intelligence-based method and device for the traceability and prediction of watershed pollution

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  • Watershed pollution traceability prediction method and device based on artificial intelligence
  • Watershed pollution traceability prediction method and device based on artificial intelligence
  • Watershed pollution traceability prediction method and device based on artificial intelligence

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Embodiment Construction

[0061] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the accompanying drawings and specific embodiments.

[0062] like figure 1 As shown, the embodiment of the present invention provides a kind of artificial intelligence-based watershed pollution traceability prediction method, including:

[0063] S101: Carry out time division for the water quality monitoring indicators in each watershed globally;

[0064] S102: Cross-calculate the divided water quality monitoring indicators to generate a correlation map between the water quality monitoring indicators;

[0065] S103: Using the correlation map as the basic data, associate and evaluate point source pollution and water quality monitoring indicators through an association rule algorithm;

[0066] S104: Take the water quality monitoring indicators in each watershed as X, and the point source polluti...

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Abstract

The invention provides a watershed pollution traceability prediction method and device based on artificial intelligence, and relates to the technical field of water environment information processing. The method comprises the following steps: carrying out cross correlation calculation on water quality monitoring indexes, taking a correlation map between the water quality indexes as input basic data, and delaying the correlation between the indexes to the correlation between point source pollution through an association rule algorithm; finally, mining potential laws of the water quality related atlas in time by using an LSTM algorithm, and realizing accurate prediction of point source pollution. The method aims to predict a main control industry point source causing water quality change, point source pollution, water quality monitoring data and an industry pollution knowledge base are used as data sets, a core algorithm in an intelligent voice technology is innovatively introduced into the environment field, algorithms such as cross correlation, association rules and a long-short term memory network are adopted, the artificial intelligence technology is used for identifying main point source pollution influencing future water quality changes.

Description

technical field [0001] The present invention relates to the field of water environment information processing and technology, in particular to an artificial intelligence-based method and device for tracing and predicting the source of watershed pollution. Background technique [0002] Data mining is the result of the development of information technology. It is the process of using various analysis tools to find and discover the relationship between models and data in massive data, and use the models and relationships to predict the potential laws of data (Xiang Xianquan et al., 2009 ). Through the mining of water environment information, the physical mechanism of the water environment process is gradually quantified, and then the water environment model is constructed. The water environment process simulation is the secondary mining of the water environment information. Therefore, water environment process simulation is one of the important methods of water environment inf...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26G06F16/36G06N3/04
CPCG06Q10/04G06Q10/06393G06Q50/26G06F16/367G06N3/044Y02A20/152
Inventor 王国强薛宝林王溥泽谢刚
Owner BEIJING NORMAL UNIVERSITY
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