Showing papers by "Jun Zhang published in 2004"
TL;DR: A high order alternating direction implicit (ADI) solution method for solving unsteady convection-diffusion problems and it is shown through a discrete Fourier analysis that the method is unconditionally stable for 2D problems.
193 citations
TL;DR: This study shows that a good quality SAI preconditioner can be constructed by using the near part matrix numerically generated in the MLFMA and can reduce the number of Krylov iterations substantially.
Abstract: In computational electromagnetics, the multilevel fast multipole algorithm (MLFMA) is used to reduce the computational complexity of the matrix vector product operations. In iteratively solving the dense linear systems arising from discretized hybrid integral equations, the sparse approximate inverse (SAI) preconditioning technique is employed to accelerate the convergence rate of the Krylov iterations. We show that a good quality SAI preconditioner can be constructed by using the near part matrix numerically generated in the MLFMA. The main purpose of this study is to show that this class of the SAI preconditioners are effective with the MLFMA and can reduce the number of Krylov iterations substantially. Our experimental results indicate that the SAI preconditioned MLFMA maintains the computational complexity of the MLFMA, but converges a lot faster, thus effectively reduces the overall simulation time.
134 citations
TL;DR: A new high‐order finite difference discretization strategy, which is based on the Richardson extrapolation technique and an operator interpolation scheme, is proposed, to solve convection diffusion equations.
Abstract: We propose a new high-order finite difference discretization strategy, which is based on the Richardson extrapolation technique and an operator interpolation scheme, to solve convection diffusion equations. For a particular implementation, we solve a fine grid equation and a coarse grid equation by using a fourth-order compact difference scheme. Then we combine the two approximate solutions and use the Richardson extrapolation to compute a sixth-order accuracy coarse grid solution. A sixth-order accuracy fine grid solution is obtained by interpolating the sixth-order coarse grid solution using an operator interpolation scheme. Numerical results are presented to demonstrate the accuracy and efficacy of the proposed finite difference discretization strategy, compared to the sixth-order combined compact difference (CCD) scheme, and the standard fourth-order compact difference (FOC) scheme. © 2003 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 20: 18–32, 2004.
56 citations
TL;DR: The experimental results of the diffusion simulations on a parallel supercomputer show that the sparse approximate inverse preconditioning strategy, which is robust and efficient with good scalability, gives a much better overall performance than the banded-block-diagonal preconditionser.
12 citations
TL;DR: This work investigates and compares the efficiency and effectiveness of a number of ILU preconditioners, and finds out that the ILUT with a dual dropping strategy gives the best overall performance when it is provided with the optimum choices of the fill-in parameter and the threshold dropping tolerance.
8 citations
16 Dec 2004
TL;DR: In this article, a Support Vector Machine (SVM) technique is proposed to perform automated ranking of potential partners in a multi-class classification problem, and the SVM-based method is advantageous in terms of generalization performance and fitness accuracy with a limited number of training datasets.
Abstract: With the rapidly increasing competitiveness in global market, dynamic alliances and virtual enterprises are becoming essential components of the economy in order to meet the market requirements for quality, responsiveness, and customer satisfaction. Partner selection is a key stage in the formation of a successful virtual enterprise. The process can be considered as a multi-class classification problem. In this paper, The Support Vector Machine (SVM) technique is proposed to perform automated ranking of potential partners. Experimental results indicate that desirable outcome can be obtained by using the SVM method in partner selections. In comparison with other methods in the literatures, the SVM-based method is advantageous in terms of generalization performance and the fitness accuracy with a limited number of training datasets.
6 citations
Journal Article•
TL;DR: The experimental results show that text retrieval based on SCD may enhance the retrieval accuracy and reduce the storage cost, compared with the popular text retrieval technique based on latent semantic indexing with singular value decomposition.
Abstract: We examine text retrieval strategies using the sparsified concept decomposition matrix. The centroid vector of a tightly structured text collection provides a general description of text documents in that collection. The union of the centroid vectors forms a concept matrix. The original text data matrix can be projected into the concept space spanned by the concept vectors. We propose a procedure to conduct text retrieval based on the sparsified concept decomposition (SCD) matrix. Our experimental results show that text retrieval based on SCD may enhance the retrieval accuracy and reduce the storage cost, compared with the popular text retrieval technique based on latent semantic indexing with singular value decomposition.
5 citations
16 Dec 2004
TL;DR: In this paper, the centroid vector of a tightly structured text collection provides a general description of text documents in that collection, and the union of the centro vectors forms a concept matrix.
Abstract: We examine text retrieval strategies using the sparsified concept decomposition matrix. The centroid vector of a tightly structured text collection provides a general description of text documents in that collection. The union of the centroid vectors forms a concept matrix. The original text data matrix can be projected into the concept space spanned by the concept vectors. We propose a procedure to conduct text retrieval based on the sparsified concept decomposition (SCD) matrix. Our experimental results show that text retrieval based on SCD may enhance the retrieval accuracy and reduce the storage cost, compared with the popular text retrieval technique based on latent semantic indexing with singular value decomposition.
5 citations
01 Jan 2004
TL;DR: This work conducts a comparable study on the properties and performance of the SAI preconditioners using the different sparsity patterns for solving some sparse linear systems.
Abstract: Sparse approximate inverse (SAI) techniques have recently emerged as a new class of parallel preconditioning techniques for solving large sparse linear systems on high performance computers The choice of the sparsity pattern of the SAI matrix is probably the most important step in constructing an SAI preconditioner Both dynamic and static sparsity pattern selection approaches have been proposed by researchers Through a few numerical experiments, we conduct a comparable study on the properties and performance of the SAI preconditioners using the different sparsity patterns for solving some sparse linear systems