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Air quality index prediction method based on spatial and temporal distribution characteristics

An air quality index and air quality technology, applied in special data processing applications, electrical digital data processing, instruments, etc., can solve problems such as air index predictions and regional air index predictions that cannot be observed.

Active Publication Date: 2015-08-19
吉奥时空信息技术股份有限公司
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Problems solved by technology

[0007] The present invention mainly solves the technical problems existing in the prior art that the air index cannot be accurately predicted for areas without observation stations and the air index cannot be predicted for fine-grained time periods; it provides an air quality based on time-space distribution characteristics Exponential Forecasting Method

Method used

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  • Air quality index prediction method based on spatial and temporal distribution characteristics
  • Air quality index prediction method based on spatial and temporal distribution characteristics
  • Air quality index prediction method based on spatial and temporal distribution characteristics

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Embodiment

[0049] figure 1 It is the air quality index prediction method based on the temporal and spatial distribution characteristics of the present invention. The method mainly includes three major steps, which are the sample acquisition step, the time series prediction step, and the kriging interpolation step, which will be introduced separately below.

[0050] 1. Sample acquisition

[0051] Obtain the latitude and longitude coordinates of the air quality monitoring stations in the area to be predicted, and record the air quality index obtained at the same time by each air quality monitoring station in the recording area at regular intervals to obtain air quality sample data; in this embodiment, each The time interval between sampling points is preferably 6 hours. In order to ensure the integrity of the training samples, the monitoring site has missing historical data, fill in the missing records, and obtain n×m samples.

[0052] 2. Time series forecasting

[0053] According to th...

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Abstract

The invention relates to an air quality index prediction method, in particular to an air quality index prediction method based on spatial and temporal distribution characteristics. The method adopts a time series prediction method to predict time orientation, i.e. an air quality index at certain time in the future; and then, a Kriging interpolation method is adopted, and the known latitude and longitude coordinates of a monitoring site are combined with a time series prediction result to carry out interpolate estimation on the air quality index of any place of a whole area. Therefore, the air quality index prediction method has the following advantages that the complexity of a model is lowered, whole calculation time is shortened, and meanwhile, the accuracy of the model is guaranteed; and in addition, the air quality indexes in multiple time periods in one day at each place within the area can be more accurately predicted.

Description

technical field [0001] The invention relates to an air quality index prediction method, in particular to an air quality index prediction method based on temporal and spatial distribution characteristics. Background technique [0002] Air is a substance that the living things on the earth depend on for survival, and it is an essential substance. Ambient air quality is closely related to people's daily life, and it also plays an important role in the comprehensive evaluation of urban environment. However, with the development of human civilization and economy, air pollution is becoming more and more serious. How to improve air quality and reasonably carry out air environment quality prediction and early warning has become more and more important. According to the local air quality prediction results, people can take corresponding measures such as Wear a mask, try to avoid going out, etc., to protect yourself from air pollutants. [0003] The air quality index is represented ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 沈满吴杰刘琳尹琴陈彬张龙黄俊韬杨曦
Owner 吉奥时空信息技术股份有限公司
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