Urban VOCs total pollution time sequence prediction method and system, storage medium and equipment

A time series prediction and total amount technology, applied in neural learning methods, stochastic CAD, probabilistic CAD, etc., can solve problems such as inconvenient operation, inability to meet comprehensive monitoring requirements, and inability to be directly applied, so as to achieve the effect of improving reasoning speed

Pending Publication Date: 2022-01-11
合肥综合性国家科学中心人工智能研究院
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Problems solved by technology

It has the advantages of real-time measurement of large-scale air pollution, but the system is complex, inconvenient to operate, and expensive, which cannot meet the needs of comprehensive monitoring
[0005] (3) Measurement at fixed monitoring stations, using a variety of pollution sensors deployed in sensitive areas and key areas of industrial parks for pollution monitoring, which collects many types of data and has high measuremen

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  • Urban VOCs total pollution time sequence prediction method and system, storage medium and equipment
  • Urban VOCs total pollution time sequence prediction method and system, storage medium and equipment
  • Urban VOCs total pollution time sequence prediction method and system, storage medium and equipment

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[0049] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments.

[0050] Such as figure 1 As shown, the urban VOCs pollution total amount time-series prediction method described in the present embodiment performs the following steps by computer equipment,

[0051]Step 1: Preprocess the monitoring data of total volatile organic compounds, so that the data can be embedded in projections, including location information, which not only includes year, month, and day information, but also includes special information such as holidays.

[0052] Step 2: First perform convolution pooling operation on the obtained data to ...

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Abstract

The invention discloses an urban VOCs total pollution time sequence prediction method and system, a storage medium and equipment, and the method comprises the steps: preprocessing total VOCs monitoring data, embedding the data for projection, wherein the data comprises position information including year, month and day information, and also including the setting information of holidays and festivals; performing convolution pooling on the obtained data, reducing redundant data, generating an attention probability matrix through a sparse full-self-attention mechanism in an encoder to obtain a feature map, inputting the feature map once repeatedly to obtain the feature map, and transmitting the feature map to a decoder; cutting half of the data, inputting the data, performing the same operation, splicing the feature maps obtained twice to form a finally obtained feature map, and transmitting the finally obtained feature map to the decoder; and masking the data, inputting the data into the decoder, and obtaining a prediction result by the decoder according to the masked input and the prediction result obtained in the previous step. A longer time sequence can be processed, and the information of the time sequence can be extracted more effectively.

Description

technical field [0001] The invention relates to the technical field of environmental monitoring, in particular to a time-series prediction method, system, storage medium and equipment for the total amount of urban VOCs pollution. Background technique [0002] As the scale of the chemical industry expands, chemical pollution tends to rise and aggravate. The environmental protection situation of the chemical industry is severe, and the emission of harmful chemical gas pollutants characterized by volatile organic compounds has become increasingly prominent. At the same time, frequent regional air pollution problems such as haze are closely related to the substandard discharge of industrial waste gas. In response to this problem, a number of technologies have been developed for the monitoring of industrial harmful pollutant gases, mainly including: [0003] (1) Gas chromatography detection, gas chromatography is a laboratory standard analysis method through chromatographic anal...

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Application Information

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IPC IPC(8): G06F30/27G06F17/16G06N3/08G06F111/08
CPCG06F30/27G06F17/16G06N3/08G06F2111/08
Inventor 许镇义潘凯康宇曹洋程凡
Owner 合肥综合性国家科学中心人工智能研究院
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