Regional air pollutant concentration prediction method, terminal and readable storage medium

A technology for pollutant concentration and air pollutants, applied in the field of data processing, can solve the problems of poor nonlinear fitting ability of multiple linear regression and low accuracy of prediction effect, and achieve the effect of strong generalization ability and improvement of prediction accuracy.

Inactive Publication Date: 2018-05-18
UNIVERSTAR SCI & TECH SHENZHEN
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  • Claims
  • Application Information

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Problems solved by technology

However, the research and application of existing statistical forecasting methods are mainly based on multiple li

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  • Regional air pollutant concentration prediction method, terminal and readable storage medium
  • Regional air pollutant concentration prediction method, terminal and readable storage medium
  • Regional air pollutant concentration prediction method, terminal and readable storage medium

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Embodiment Construction

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0031] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.

[0032] In a specific implementation, the terminals described i...

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Abstract

The embodiment of the invention provides a regional air pollutant concentration prediction method, terminal and computer readable storage medium. The method includes using a calculated daily average historical pollutant concentration data set and a preprocessed daily historical meteorological data set as sample data sets, utilizing a random forest model to perform training, wherein the random forest model includes a plurality of decision trees, each decision tree being implemented by use of a multilayer feedforwad neural network; determining predicted meteorological data of a preset number ofdays in the future predicted on the same day at current time; preprocessing the predicted meteorological data; and according to the preprocessed predicted meteorological data and pollutant concentration data monitored on the same day at current time, utilizing the trained random forest model to predict pollutant concentration data of the preset number of days in the future of a region to be predicted. The regional air pollutant concentration prediction method provided by the embodiment of the invention improves regional air pollutant concentration prediction precision, and has relatively a high generalization capability.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method for predicting the concentration of regional air pollutants, a terminal and a computer-readable storage medium. Background technique [0002] In recent years, large-scale air pollution incidents have frequently occurred in most parts of my country, and the air pollution problem has seriously affected the normal life and production of the people. Common air pollutants, such as PM2.5, PM10, O3, etc., are extremely harmful to human health. Use reliable and easy-to-use air forecasting methods to predict the occurrence and change trend of air pollution, so that government departments can keep abreast of future air quality conditions, and take early response measures in the face of heavy air pollution events to ensure people's lives and health, with the minimum economic cost It is particularly important to realize the maximum social benefits at a low cost. [0003] A...

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Application Information

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IPC IPC(8): G06Q10/04G06N99/00G01N33/00G01N15/06
CPCG01N15/06G01N33/0004G06N20/00G06Q10/04
Inventor 戈燕红舒少君雷涛
Owner UNIVERSTAR SCI & TECH SHENZHEN
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