Determining the degree of environmental pollution for the power industry using artificial intelligence tools

Abstract

The technical solution concerns a method of determining the degree of environmental pollution for the field of electric power using artificial intelligence tools. The essence of the solution lies in the use of data on the concentration of particles PM10, PM2.5, NO₂, SO₂ and O₃, precipitation totals, traffic intensity, occurrence of mining areas and agricultural activity, while using specialized neural networks (15) to (17) time series of the total amount of captured fallout S (18), the amount of soluble substances in the sediment Sr (19) and the specific electrical conductivity of a 0.2% solution of soluble substances 0.2 (20) are determined. From the obtained time series, using the generalized distribution of extreme values ​​GEV (24), the maximum values ​​Sm (21), Srm (22), 0.2m (23) are determined with a probability of not exceeding 95%, while the degree of pollution for the monitored area (3) is determined by calculating the parameter p (25) and comparing it with defined intervals.

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