Tensor based approach to the numerical treatment of the parameter estimation problems in mathematical immunology
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Publication:682032
DOI10.1515/jiip-2016-0083zbMath1383.92047OpenAlexW2620753307MaRDI QIDQ682032
Dmitry A. Zheltkov, Zvi Grossman, Valeriya V. Zheltkova, Gennadii A. Bocharov, Evgenij E. Tyrtyshnikov
Publication date: 13 February 2018
Published in: Journal of Inverse and Ill-Posed Problems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/jiip-2016-0083
Nonlinear programming (90C30) Discrete approximations in optimal control (49M25) Medical epidemiology (92C60)
Related Items
Global and local optimization in identification of parabolic systems, Numerical steady state analysis of the Marchuk-Petrov model of antiviral immune response, Multiphysics modelling of immune processes using distributed parameter systems, Numerical algorithm for source determination in a diffusion-logistic model from integral data based on tensor optimization, Artificial intelligence for COVID-19 spread modeling, Global optimization based on TT-decomposition, Optimization methods for solving inverse immunology and epidemiology problems, Mathematical modeling of the Wuhan COVID-2019 epidemic and inverse problems, Global Optimization Algorithms Using Tensor Trains, Application of the Global Optimization Methods for Solving the Parameter Estimation Problem in Mathematical Immunology
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Cites Work
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