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Method and device for predicting concentration of atmospheric pollutants

A technology for air pollutants and concentration prediction, applied in the computer field, can solve problems such as inaccuracy and poor prediction effect of pollutant concentration

Inactive Publication Date: 2019-03-29
长三角环境气象预报预警中心
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Problems solved by technology

[0004] One purpose of this application is to provide a method and equipment for predicting the concentration of air

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  • Method and device for predicting concentration of atmospheric pollutants
  • Method and device for predicting concentration of atmospheric pollutants
  • Method and device for predicting concentration of atmospheric pollutants

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[0031] The application will be further described in detail below in conjunction with the drawings.

[0032] In a typical configuration of this application, the terminal, the equipment of the service network, and the trusted party all include one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0033] The memory may include non-permanent memory in computer readable media, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of computer readable media.

[0034] Computer-readable media includes permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic ran...

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Abstract

The purpose of the present application is to provide a method and a device for predicting the concentration of atmospheric pollutants. The method comprises the steps of: obtaining target feature data,wherein the target feature data comprises high altitude forecast data, surface forecast data and historical monitoring data; performing feature extraction of the historical monitoring data, inputtingthe historical monitoring data after feature extraction into a coding end of an Seq2seq model, and converting the historical monitoring data after feature extraction to a state quantity through the coding end of the Seq2seq model and transmitting the state quantity to a decoding end of the Seq2seq model; performing feature extraction of the high altitude forecast data and the surface forecast data to perform training, determining input feature data according to the training result, and inputting the input feature data into the decoding end of the Seq2seq model; and according to the output result of the decoding end, predicting the concentration of atmospheric pollutant so as to obtain a prediction result with higher accuracy.

Description

technical field [0001] The present application relates to the field of computers, in particular to a method and equipment for predicting the concentration of air pollutants. Background technique [0002] Due to the complex meteorological environment factors, the index prediction of air pollutant concentration has always been a relatively complicated problem. At present, the commonly used prediction methods include the mechanism prediction method based on the atmospheric chemical transport model and the statistical prediction method based on the machine learning model. The former has been widely used in practical engineering. However, since the atmosphere is a very complex system, it is difficult to quantify it theoretically, so there are large errors in the mechanism prediction method. [0003] At present, the forecast of the weather state and the concentration of various pollutants by the domestic meteorological bureau is obtained by the calculation of the atmospheric chem...

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Application Information

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IPC IPC(8): G01W1/10G01N33/00G06F17/18
CPCG01N33/0004G01W1/10G06F17/18
Inventor 马井会余钟奇曹钰瞿元昊潘亮许建明杨洪山
Owner 长三角环境气象预报预警中心
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