Titlebook: Numerical Computations: Theory and Algorithms; Third International Yaroslav D. Sergeyev,Dmitri E. Kvasov Conference proceedings 2020 Sprin

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0302-9743 nterconnected fields as local and global optimization, machine learning, approximation, and differential equations. A special focus is given to advanced ideas related to methods and applications using emerging computational paradigms..978-3-030-40615-8978-3-030-40616-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Are Humans Bayesian in the Optimization of Black-Box Functions?e searching for the maximum of an unknown 2D function. A set of controlled experiments with 53 subjects confirm that Gaussian Processes provide a general model to explain different patterns of learning enabled search and optimization in humans.

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Set-Membership Computation of Integrals with Uncertain Endpoints the computation of the minimum and maximum of these integrals and provides the endpoints at stake. The complexity of the resulting algorithms is discussed, it depends on the number of roots of the function to be integrated. The computation is illustrated on several examples.

艱苦地移動

Numerical Algorithms for the Parametric Continuation of Stiff ODEs Deriving from the Modeling of Com]. Starting from the procedure presented in [.], this paper illustrates further improvements of key steps that usually represents a bottleneck for the effective computation of parametric continuations and for the identification of bifurcation points.

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Multiextremal Optimization in Feasible Regions with Computable Boundaries on the Base of the Adaptivive nested algorithm in comparison with the classical nested optimization and the penalty function method, a representative numerical experiment on the test classes of multidimensional multiextremal functions has been carried out. The results of the experiment demonstrate a significant advantage of

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Epidemic Spreading Curing Strategy Over Directed Networks it. Differently from a previous work where we proposed a GA for solving the OCP problem on undirected networks, here we consider the formulation of the optimization problem for directed weighted networks and extend the GA method to deal with not symmetric adjacency matrices that are not diagonally