Air pollutant concentration precise monitoring method and system based on tensor representation

A technology for expressing air pollutants and vectors, applied in design optimization/simulation, special data processing applications, complex mathematical operations, etc., can solve the problems of high computational complexity, time-varying laws of air pollutants that cannot be directly described, and unintuitive internals Mechanism and other issues

Pending Publication Date: 2022-01-14
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, because the machine learning algorithm focuses on fitting data and its unintuitive internal mechanism, the computational complexity in the machine learning model is high, and the machine learning algorithm combined with the historical data of air pollutants is often simply used as the input of the model. The time-varying law of air pollutants cannot be directly described, which makes improving the spatial resolution of air pollutant concentrations and analyzing the time-varying characteristics of air pollutant concentrations two independent issues

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  • Air pollutant concentration precise monitoring method and system based on tensor representation
  • Air pollutant concentration precise monitoring method and system based on tensor representation
  • Air pollutant concentration precise monitoring method and system based on tensor representation

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specific Embodiment approach

[0072] A specific implementation of a method for precise monitoring of air pollutant concentration based on tensor representation, the method includes:

[0073] Step 1, tensorized representation of air quality data. The air quality monitoring stations are sparsely distributed in the geographical space of the city. The air quality monitoring stations will obtain the concentration of various pollutants in the air in real time, including PM2.5, PM10, ozone and other data. The spatial distribution of air quality monitoring stations, the time series of pollutant concentrations and the concentration of various air pollutants in the air are described by a tensor, and a fourth-order air quality tensor is obtained.

[0074] Step 2, construct the tensor singular function of the air quality tensor. Since the concentration of pollutants in air quality is stored in a table mode, the representation of air quality monitoring sites in geographic space needs to be described by a function mode...

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Abstract

The invention belongs to the technical field of air pollution monitoring, and particularly relates to an air pollutant concentration precise monitoring method and system based on tensor representation, and the method comprises the steps: obtaining the air quality data of a to-be-detected point in real time, inputting the obtained air quality data into a monitoring model, and obtaining a monitoring result; marking the monitoring point according to the monitoring result; According to the method, the multi-source data and the space-time air pollutant concentration data are fused to carry out tensor completion, so that high-precision tensor data are obtained.

Description

technical field [0001] The invention belongs to the technical field of air pollution monitoring, and in particular relates to a method and system for precise monitoring of air pollutant concentration based on tensor representation. Background technique [0002] Along with the process of urbanization and industrialization, more and more environmental pollution problems have also attracted public attention. Air pollution is an important source of environmental pollution that affects the health of residents. In order to monitor and prevent air pollutants, many cities have established their own air quality monitoring stations, which will obtain the concentration of air pollutants in the city in real time. By analyzing and studying the concentration of air pollutants in cities, scientific research institutions can effectively assist the government in formulating environmental protection policies that are in line with the public interest. [0003] Grid monitoring needs to obtain...

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Application Information

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IPC IPC(8): G06F30/20G06F17/16G06F113/08
CPCG06F30/20G06F17/16G06F2113/08
Inventor 张晓霞胡峻嘉钟福金
Owner CHONGQING UNIV OF POSTS & TELECOMM
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