Atmospheric PM2.5 concentration prediction method and system based on two-stage non-negative Lasso model

A concentration prediction and stage technology, applied in the direction of measurement devices, design optimization/simulation, CAD numerical modeling, etc., can solve problems such as prediction errors, unguaranteed model coefficients, and business inconsistencies

Active Publication Date: 2020-08-25
CHINESE ACAD OF ENVIRONMENTAL PLANNING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] 1) It is impossible to guarantee that the positive and negative values ​​of the model coefficients are consistent with the actual business;
[0007] 2) It cannot be guaranteed that all model coefficients are not zero, that is, it cannot be guaranteed that each c

Method used

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  • Atmospheric PM2.5 concentration prediction method and system based on two-stage non-negative Lasso model
  • Atmospheric PM2.5 concentration prediction method and system based on two-stage non-negative Lasso model
  • Atmospheric PM2.5 concentration prediction method and system based on two-stage non-negative Lasso model

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Embodiment 1

[0172] The present invention also provides a kind of atmospheric PM based on two-stage non-negative Lasso model 2.5 The concentration prediction system is characterized in that the system includes:

[0173] The grid division module is used to divide a region into multiple grid areas at the spatial level, and use the bottom-up spatialization method for each grid area to calculate the annual carbon dioxide emission data in the grid area , as the CO2 emissions inventory data for the grid area; and

[0174] A prediction module, for inputting carbon dioxide emission inventory data of a certain grid area in the region to a pre-trained two-stage non-negative Lasso model, and outputting a first prediction result and a second prediction result;

[0175] Add the first prediction result and the second prediction result to get the PM of the area 2.5 Concentration data prediction results.

Embodiment 2

[0177] Embodiment 2 of the present invention may further provide a computer device, including: at least one processor, a memory, at least one network interface, and a user interface. The individual components in the device are coupled together via a bus system. It can be understood that the bus system is used to realize the connection communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus and a status signal bus.

[0178] Wherein, the user interface may include a display, a keyboard, or a pointing device (for example, a mouse, a trackball (trackball), a touch panel, or a touch screen, and the like.

[0179] It can be understood that the memory in the disclosed embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. Wherein, the non-volatile memory may be a read-only memory (Read-Only Memory, ROM), a programmable read-on...

Embodiment 3

[0188] Embodiment 3 of the present invention may also provide a non-volatile storage medium for storing computer programs. When the computer program is executed by the processor, various steps in the foregoing method embodiments can be realized.

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Abstract

The invention belongs to the technical field of atmospheric pollutant concentration prediction, and specifically relates to an atmospheric PM2.5 concentration prediction method based on a two-stage non-negative Lasso model. The method comprises the following steps: dividing a certain region into a plurality of grid regions on a space level, and calculating annual carbon dioxide emission data in each grid region by utilizing a bottom-to-top spatialization method to serve as carbon dioxide emission list data of the grid region; inputting real-time acquired carbon dioxide emission data of a certain region of the region into a pre-trained two-stage non-negative Lasso model, and outputting a first prediction result and a second prediction result; and adding the first prediction result and the second prediction result to obtain a PM2.5 concentration data prediction result of the region, thereby realizing atmospheric PM2.5 concentration prediction of the region.

Description

technical field [0001] The invention belongs to the technical field of atmospheric pollutant concentration prediction, in particular, relates to a two-stage non-negative Lasso model-based atmospheric PM 2.5 Concentration prediction method and system. Background technique [0002] PM 2.5 It refers to the particulate matter with an aerodynamic equivalent diameter of less than or equal to 2.5 microns in the environment. The higher the concentration in the air, the more serious the air pollution. With the rapid advancement of industrialization, the phenomenon of atmospheric smog is becoming more and more serious, PM 2.5 It is one of the main culprits that cause smog. Its particle size is small, can be suspended in the air for a long time and spread, and can carry toxic and harmful substances into the respiratory tract and lungs. Regular large-scale smog affects people's health. Daily travel poses a direct threat to human health. PM 2.5 It is the main component of smog, and ...

Claims

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Application Information

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IPC IPC(8): G06F30/20G01N15/06G06F111/10
CPCG01N15/06G06F30/20G06F2111/10
Inventor 蔡博峰刘译璟鲁瑞魏太云曹丽斌伍鹏程庞凌云
Owner CHINESE ACAD OF ENVIRONMENTAL PLANNING
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