@misc{Kuczewski_Bartosz_Computational,
 author={Kuczewski, Bartosz},
 howpublished={online},
 publisher={Zielona Góra: Oficyna Uniwersytetu Zielonogórskiego},
 language={eng},
 abstract={In this dissertation we consider T-optimum designs for maximizing the likelihood of discrimination between two and more rival dynamic multi-response models. Our main goal was to develop the background needed to solve computational problems and to provide efficient numerical methods of constructing T-optimum designs for dynamic processes described by ordinary and partial differential equations. A starting point for this project was the works by Atkinson and Fedorov who proposed an algorithm for generating approximations to T-optimum designs, which has remained since then the only known computational tool in this context. But the major drawback of the method was the lack of its convergence analysis. In fact, the method, as it was formulated, was not globally convergent. The obvious task of the present research was thus to look closely at Fedorov's algorithm.},
 abstract={This resulted in the formulation of a family of methods which combine some features of the original Fedorov method and, at the same time, possess global convergence properties. The most important, a novel relaxation algorithm RATO (Relaxation Algorithm for T-Optimality) is presented and its convergence in a finite number of steps is proved. Moreover, a thorough analysis of additional numerical problems associated with the RATO scheme is presented, including a proposition of appropriate regularization for non-smooth functions being optimized. The proposed solutions have been tested on practical process engineering examples, i.e., chemical kinetics or air pollution modelling, thereby indicating their potential applications in numerous disciplines.},
 type={rozprawa doktorska},
 type={książka},
 title={Computational aspects of discrimination between models of dynamic systems},
 keywords={układy dynamiczne, optymalne planowanie eksperymentu, identyfikacja strukturalna, algorytmy numeryczne, problemy minimaksowe, T-optymalność},
}