Use of Artificial Neural Networks to Predict Levels of Air Pollution and Water Bodies
Keyword(s):
Describes the process of creating a simple and effective tool for predicting the quality of air and water bodies. Artificial neural networks are an effective tool for predicting the concentrations of suspended particles of heavy metals. The correct choice of input and output data with a clear relationship between them is necessary to obtain reliable results. Emphasis is placed on predictions of heavy metals due to permissible level of these pollutants, which often was exceeded in Tula. For given conditions, the best results are obtained using a single-layer perception with a back propagation algorithm.
2021 ◽
2019 ◽
Vol 11
(3)
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2017 ◽
Vol 43
(4)
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pp. 26-32
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2019 ◽
Vol 8
(3)
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pp. 4645-4650
2019 ◽
Vol 14
(2)
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pp. 285-315
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