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Matrix models and parquet approximation
Shishanin Andrei O.
-dimensional hermitian matrix models. We discuss how the parquet approximation reproduces the results of a planar
Approximate methods of the decision differential the equations for continuous models of economy
Vorontsova V., Uy G.
© 2015, Asian Social Science. All rights reserved. The review of some models of economy based
Approximate methods of the decision differential the equations for continuous models of economy
Vorontsova V., Uy G.
© 2015, Asian Social Science. All rights reserved. The review of some models of economy based
On existence, stability and many-particle approximation of solutions of 1D Hughes' model with linear costs
Andreianov B., Rosini M.D., Stivaletta G.
This paper deals with the one-dimensional formulation of Hughes' model for pedestrian flows
Approximation of the Dependency of Trace Elements Concentrations in Internal Media upon their Contents in Environment Objects
, and a Boltzmann function were applied to evaluate the approximation degree by different models
Numerical methods of the decision differential the equations for continuous models of economy
Vorontsova V., Gorskaya T.
equations of continuous models of economy in work the approximate method is offered and reasonable
Nanostructural magnetism of polymeric fullerene crystals
Sheka E.F., Zaets V.A., Ginzburg I.Ya.
the unrestricted Hartree-Fock approximation and the semiempirical AM1 method are presented. It is shown
The convergence of approximation attractors to attractors for Bingham model with periodical boundary conditions on spatial variables
Ashyralyev A., Zvyagin V., Turbin M.
of approximation problems to trajectory and global attractors of the Bingham model on the torus. For research
Approximating blocking probabilities for multiservice network link with unicast and multicast connections
Plaksina O.N., Samouylov K.E.
connections. We model the link as a multi-stream loss system and study an approximate method for computing
New Algorithm for Building Effective Model from Prediction Models Using Parallel Data
Gasitashvili, Z., Phkhovelishvili, M., Archvadze, N.
Building much more effective new hybrid models from prediction models, using parallel data

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