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Near-ground environment element prediction model training and prediction method based on machine learning

A technology for environmental elements and prediction models, which is applied in the field of machine learning and can solve problems such as the inability to directly provide spatiotemporal distribution and change trends.

Inactive Publication Date: 2021-07-30
TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, satellite remote sensing monitoring cannot directly provide the temporal and spatial distribution and change trends of environmental factors such as ground PM2.5 / 10 concentration, ozone concentration, and temperature.

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  • Near-ground environment element prediction model training and prediction method based on machine learning
  • Near-ground environment element prediction model training and prediction method based on machine learning

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Embodiment Construction

[0033] In order to make the objects, technical solutions, and advantages of the present invention more clearly, the technical solutions in the embodiments of the present invention will be described in contemplation in the embodiments of the present invention, and will be described, and the embodiments described herein will be described. It is a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, there are all other embodiments obtained without making creative labor without making creative labor premises.

[0034] As mentioned earlier, traditional monitoring methods have ground monitoring and remote sensing monitoring. Ground monitoring can directly get the ground PM2.5 / 10, ozone, temperature environmental elements value concentration and its accurate information of time change, but the ground monitoring cost is expensive and can only be carried out in a limited surface site. Satellite remote sensing dat...

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Abstract

The embodiment of the invention provides a training method and a prediction method for a prediction model of near-ground environmental elements. The training method comprises the following steps: acquiring remote sensing image data, meteorological monitoring data, air quality monitoring data and environmental data of a first region; acquiring monitoring values of near-ground environment elements of the first region; generating a training sample, in which at least part of data in the remote sensing image data and at least part of data in the meteorological monitoring data, the air quality monitoring data and the environment data serve as model input data, and the monitoring values of the near-ground environment elements serve as label values; and training a near-surface environment element prediction model by using the training sample.

Description

Technical field [0001] The present invention relates to the fields and environmental monitoring areas of machine learning, in particular, relating to the training and prediction methods of near-ground environmental elements based on machine learning. Background technique [0002] With the rapid development of economy, industrialization and urbanization process accelerated environmental support, the pressure of air pollution is becoming more serious. Monitoring environmental elements such as PM2.5 / 10 concentration, ozone concentration, temperature, and discloses its distribution law on time and space, which is important for conducting atmospheric pollution characteristics. [0003] Currently, common monitoring methods have ground monitoring and remote sensing monitoring. Ground Monitoring Based on the observation station for all-weather continuous observations, it is possible to directly obtain the near-ternary PM2.5 / 10, ozone, temperature environmental elements value concentr...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G01W1/10G06N3/04G06N3/08G06N20/00
CPCG06Q10/04G06N20/00G06N3/084G01W1/10G06N3/045
Inventor 黄小猛张博梁逸爽
Owner TSINGHUA UNIV