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This article is cited in 1 scientific paper (total in 1 paper)
Geoinfromatics
Forecasting of Microcystis aeruginosa seasonal dynamics using the fuzzy logic and fuzzy neural networks
A. O. Gayazovaa, S. M. Abdullaevb a Municipal enterprise “Production association of water supply and
distribution” (Chelyabinsk, Russian Federation)
b South Ural State University (Chelyabinsk, Russian Federation)
Abstract:
At determination of coefficient of the hydraulic conductivity of oil layer by the method of the hydrodynamic listening of mining holes there is a need for solving the inverse task of filtration. It is thus important to set the task so that to provide the uniqueness of the decision. In this article are defined the conditions which are sufficient for the uniqueness of the inverse problem.
Keywords:
M. aeruginosa, àlgae bloom forecasting, quasi-periodic oscillations, linear extrapolation, fuzzy logic, fuzzy artificial neural networks.
Received: 05.11.2012
Citation:
A. O. Gayazova, S. M. Abdullaev, “Forecasting of Microcystis aeruginosa seasonal dynamics using the fuzzy logic and fuzzy neural networks”, Vestn. YuUrGU. Ser. Vych. Matem. Inform., 2012, no. 2, 5–11
Linking options:
https://www.mathnet.ru/eng/vyurv122 https://www.mathnet.ru/eng/vyurv/y2012/i2/p5
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Abstract page: | 143 | Full-text PDF : | 57 | References: | 31 |
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