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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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.
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Property | Measurement | Unit |
Diameter | 10.0 | µm |
tensile | MPa | |
Particle size | Pa | |
strength | 10 |
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