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This paper deals with the basic preconditioning and deflation variants of the FETI-1 and TFETI-1 methods, with (T)FETI-1 with deflation being called (T)FETI-2. It also presents the results of numerical experiments performed on a simple benchmark 2D problem of linear elasticity to compare the computational efficiency of FETI-1 and TFETI-1 and each variant of their preconditioning or deflation in terms of number of executed CG iterations.
This paper deals with wildfire identification in the Alaska regions as a semantic segmentation task using support vector machine classifiers. Instead of colour information represented by means of BGR channels, we proceed with a normalized reflectance over 152 days so that such time series is assigned to each pixel. We compare models associated with -loss and -loss functions and stopping criteria based on a projected gradient and duality gap in the presented benchmarks.
PERMON (Parallel, Efficient, Robust, Modular, Object-oriented, Numerical) is a newly emerging collection of software libraries, uniquely combining Quadratic Programming (QP) algorithms and Domain Decomposition Methods (DDM). Among the main applications are contact problems of mechanics. This paper gives an overview of PERMON and selected ingredients improving scalability, demonstrated by numerical experiments.
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