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  • The paper deals with algorithms for estimation of non-linear regression parameters. Stochastic population-based algorithm with competition was implemented and compared with standard gradient algorithm commonly used for least-squares estimates. The results show that this stochastic algorithm found the global minimum in most tasks where gradient algorithm fails. Such population-based algorithms can be used as a tool for estimation of non-linear regression parameters, especially in tasks of higher difficulty level or in tasks when suitable starting values for gradient method are not available.
  • The paper deals with algorithms for estimation of non-linear regression parameters. Stochastic population-based algorithm with competition was implemented and compared with standard gradient algorithm commonly used for least-squares estimates. The results show that this stochastic algorithm found the global minimum in most tasks where gradient algorithm fails. Such population-based algorithms can be used as a tool for estimation of non-linear regression parameters, especially in tasks of higher difficulty level or in tasks when suitable starting values for gradient method are not available. (en)
  • Algoritmy pro odhad parametrů nelineárních modelů. Popsán stochastický algoritmus založený na soutěži lokálních heuristik´. (cs)
Title
  • Robust Algorithm for Estimation of Parameters in Non-linear Regression Model
  • Robustní algoritmus pro odhad parametrů nelineárních regresních modleů (cs)
  • Robust Algorithm for Estimation of Parameters in Non-linear Regression Model (en)
skos:prefLabel
  • Robust Algorithm for Estimation of Parameters in Non-linear Regression Model
  • Robustní algoritmus pro odhad parametrů nelineárních regresních modleů (cs)
  • Robust Algorithm for Estimation of Parameters in Non-linear Regression Model (en)
skos:notation
  • RIV/61988987:17310/05:00000172!RIV07-MSM-17310___
http://linked.open...avai/riv/aktivita
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  • P(GA201/05/0284), Z(MSM6198898701)
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  • 541302
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  • RIV/61988987:17310/05:00000172
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  • global optimization; stochastic algorithms; competing heuristics; non-linear regression; NIST datasets; MATLAB (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...i/riv/kodPristupu
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  • [DEE36796AD5C]
http://linked.open...i/riv/mistoVydani
  • Praha
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  • Technical Computing Prague 2005
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  • Tvrdík, Josef
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  • Přednáška
http://linked.open...n/vavai/riv/zamer
https://schema.org/isbn
  • 80-7080-577-3
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  • 17310
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