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Matem. Mod., 2007, Volume 19, Number 12, Pages 43–51 (Mi mm1225)  

This article is cited in 3 scientific papers (total in 3 papers)

Construction of approximate neural network models according to heterogeneous data

A. N. Vasilyev, D. A. Tarkhov

Saint-Petersburg State Polytechnical University

Abstract: Neural network approach to the robust mathematical model construction according to heterogeneous pieces of information (equations, conditions, experimental data, etc.) is considered. The case of ordinary differential equations and the case of partial differential equations and possible generalizations as well are key problems in the paper. Some model examples are given.

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Received: 18.12.2006

Citation: A. N. Vasilyev, D. A. Tarkhov, “Construction of approximate neural network models according to heterogeneous data”, Matem. Mod., 19:12 (2007), 43–51

Citation in format AMSBIB
\Bibitem{VasTar07}
\by A.~N.~Vasilyev, D.~A.~Tarkhov
\paper Construction of approximate neural network models according to heterogeneous data
\jour Matem. Mod.
\yr 2007
\vol 19
\issue 12
\pages 43--51
\mathnet{http://mi.mathnet.ru/mm1225}
\zmath{https://zbmath.org/?q=an:1140.68450}


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    Citing articles on Google Scholar: Russian citations, English citations
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    This publication is cited in the following articles:
    1. A. N. Vasilev, “Matematicheskoe modelirovanie raspredelennykh sistem s pomoschyu neironnykh setei”, Matem. modelirovanie, 19:12 (2007), 32–42  mathnet  zmath
    2. Vasilev A.N., Tarkhov D.A., “Matematicheskie modeli sistem s intervalno zadannymi parametrami na osnove geterogennykh neironnykh setei. Prodolzhenie temperaturnogo polya – klassicheskaya postanovka zadachi”, Neirokompyutery: razrabotka, primenenie, 2012, no. 11, 056–059  elib
    3. Vasilev A.N., Tarkhov D.A., “Parametricheskie neirosetevye modeli klassicheskikh i neklassicheskikh zadach dlya uravneniya teploprovodnosti”, Nauchno-tekhnicheskie vedomosti SPbGPU, 2012, no. 153, 136–144  elib
  • Математическое моделирование
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