Ozonosphere forecasting algorithm based on artificial intelligence

A technology of artificial intelligence and the ozone layer, applied in the direction of calculation, neural learning methods, computer-aided design, etc., can solve the problems of complex causes of atmospheric ozone pollution, cumbersome mathematical modeling process, inconvenient ozone concentration, etc., to achieve accurate and efficient ozone concentration, High generalization, accurate and efficient prediction effect

Active Publication Date: 2022-01-07
NAT UNIV OF DEFENSE TECH
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AI Technical Summary

Problems solved by technology

However, ozone pollution has "increased instead of falling", becoming an urgent problem to be solved in the next stage of air pollution prevention and control
The causes of atmospheric ozone pollution are complex, which brings great difficulties to the actual treatment work
[0004] At present, there are still some problems in the existing artificial intelligence-based ozone layer forecasting algorithm: the mathematical modeling process is cumbersome, it is inconvenient to accurately forecast the ozone concentration, and it is not conducive to environmental protection. Therefore, we propose an artificial intelligence-based ozone layer forecasting algorithm

Method used

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  • Ozonosphere forecasting algorithm based on artificial intelligence
  • Ozonosphere forecasting algorithm based on artificial intelligence
  • Ozonosphere forecasting algorithm based on artificial intelligence

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Embodiment 1

[0047] see figure 1 , the present invention provides a kind of technical scheme: the ozone layer prediction algorithm based on artificial intelligence, comprises the following steps:

[0048] S1. Establish an ozone concentration monitoring station: select a location that has no impact on the surrounding environment and the discharge of active pollutants as the ozone concentration monitoring station;

[0049] S2. collect and obtain historical meteorological data: obtain the daily concentration data of each ozone concentration monitoring site history every day, the daily concentration data predicted every day of each ozone concentration monitoring site history and the reference corresponding to the history of each ozone concentration monitoring site every day As a result, the reference result corresponding to the history of each ozone concentration monitoring site every day is the difference between the daily concentration data of each ozone concentration monitoring site history...

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Abstract

The invention discloses an ozonosphere forecasting algorithm based on artificial intelligence. The ozonosphere forecasting algorithm comprises the following steps: S1, establishing an ozone concentration monitoring station; S2, collecting and acquiring historical meteorological data; S3, selecting influence factors; S4, carrying out preliminary prediction on the O3-8 h value of one day; S5, establishing a new hyperchaotic system; S6, establishing an artificial neural network; S7, establishing a chaotic artificial neural network; and S8, performing long-term and short-term forecasting by using the chaos artificial neural network. The research process of a traditional numerical weather forecasting method can be simplified, the traditional numerical weather forecasting method is often complex and high in calculation requirement, and the CANN operation adopted by the method is similar to other neural networks in that the CANN operation does not depend on the complex relation between parameters and output, but depends on continuous changes of weights, therefore, parameters are closely associated with output, and tedious mathematical modeling is avoided.

Description

technical field [0001] The invention belongs to the technical field of ozone layer forecasting, and in particular relates to an artificial intelligence-based ozone layer forecasting algorithm. Background technique [0002] The ozone layer is the stratosphere of the atmosphere where the concentration of ozone is high. The part with the greatest concentration is located at an altitude of 20-25 kilometers. If the ozone of the ozone layer is corrected to the standard situation, its thickness is only about 3 millimeters on average. Ozone content varies with latitude, season and weather. Ultraviolet radiation is absorbed by ozone at high altitudes, which has a warming effect on the atmosphere. At the same time, it protects the living things on the earth from the damage of far ultraviolet radiation. The small amount of ultraviolet radiation that passes through has a bactericidal effect and is of great benefit to living things. [0003] With the continuous deepening of structural...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06F30/28G06N3/04G06N3/08G06F113/08G06F119/14
CPCG06F30/27G06F30/28G06N3/0418G06N3/084G06F2113/08G06F2119/14Y02A90/10
Inventor 汪浩笛史剑杜辉张文郭海龙曾智张雪艳
Owner NAT UNIV OF DEFENSE TECH
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