J
Jun Zhang
Researcher at University of Kentucky
Publications - 199
Citations - 4299
Jun Zhang is an academic researcher from University of Kentucky. The author has contributed to research in topics: Multigrid method & Preconditioner. The author has an hindex of 37, co-authored 188 publications receiving 4031 citations. Previous affiliations of Jun Zhang include Southwest Petroleum University & University of Minnesota.
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Combining ant colony optimization with 1-opt local search method for solving constrained forest transportation planning problems
TL;DR: A two-stage approach combining the ant colony optimization (ACO) algorithm and a 1-opt local search to solve forest transportation planning problems (FTPPs) considering fixed and variables costs and sediment yields expected to erode from road surfaces as side constraints indicates the usefulness of this approach to provide managers with an efficient tool to address large-scale transportation problems.
Journal ArticleDOI
A Comparative Study on Dynamic and Static Sparsity Patterns in Parallel Sparse Approximate Inverse Preconditioning
Kai Wang,Sangbae Kim,Jun Zhang +2 more
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.
Proceedings ArticleDOI
Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under biGaussian assumption
TL;DR: In this paper, the sampling theorem on band-limited spherical harmonics is used to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR).
Proceedings ArticleDOI
Parallel simulation of multiple proteins through a bioreactor coupled with biochemical reactions
TL;DR: A parallel numerical solution to investigate multiple growth factors competitive binding within a bioreactor, an in vitro flow cell culture system is presented and it is found that heparin or possibly other solution binding agents can effectively prevent fibroblast growth factor-2 capture under flow, but only at high concentrations.
Proceedings ArticleDOI
An online condition number query system
Dianwei Han,Shuting Xu,Jun Zhang +2 more
TL;DR: This work proposes to use data mining techniques to estimate the condition number of a given sparse matrix using Support Vector Machine (SVM) and support vector regression (SVR) to predict its condition number.