The technique for the operative forecast of a high level of pollution of atmospheric air in cities is offered on the basis of use neural networks technologies. Approaches to revealing sets of the meteorological parameters causing formations of high ground concentration of impurity are developed.
полимерные производства, прогноз уровня загрязнения, атмосферный воздух, нейронные сети, Polymeric manufactures, the forecast of a level of pollution, quality of atmospheric air, neural networks
1. RD 52.04.306-92 Rukovodstvo po prognozu zagryazneniya vozduha v gorodah, Moskva, 1992.
2. Prognozirovanie vysokih urovney zagryazneniya vozduha v gorodah i promyshlennyh regionah.// Sovremennye issledovaniya GGO, T1. Moskva, 1999. C.127-143.
3. Tunakova Yu.A., Novikova S.V., Shagidullina R.A., Shmakova Yu.A. Vestnik Kazanskogo tehnologicheskogo universiteta, 12, 71-74 (2012).
4. Tunakova Yu.A., Novikova S.V., Shagidullina R.A., Shmakova Yu.A. Vestnik Kazanskogo tehnologicheskogo universiteta, 13, 183-188 (2012).
5. S. Osovskiy Neyronnye seti dlya obrabotki informacii. Finansy i statistika, Moskva, 2002, 344s.
6. R. Kalan Osnovnye koncepcii neyronnyh setey. «Vil'yams», Moskva, 2001, 287s.
7. Kruglov V.V., Borisov V.V. Iskusstvennye neyronnye seti. Teoriya i praktika. Goryachaya liniya - Telekom,Moskva, 2002.
8. Teuvo Kohonen Self-Organizing Maps. Izd-vo Springer - Verlag, 2001,3- izdanie. 501s.
9. RD 52.04.52-85 Regulirovanie vybrosov pri neblagopriyatnyh meteorologicheskih usloviyah, Moskva,1985.
