Linking of direct and iterative methods in Markovian models solving

An article identifies and assesses an effectiveness of two different methods applied to solve linear equations systems which result while modeling of computer networks and systems with Markov chains. The paper considers both the hybrid of direct methods as well as classic one of iterative methods. Two varieties of Gauss elimination will be considered as an example of direct methods: the LU factorization method and the WZ factorization method. Gauss-Seidel iterative method will be discussed. That issue points in preconditioning and matrix division into blocks where blocks will be solved applying direct methods. The paper presents an impact of liked methods on both time and accuracy of vector probability determining regarding particular networks and computer systems occurring.