2 citations · 4 across the 4 of their papers we have counts for
4 papers
Low-discrepancy Sampling in the Expanded Dimensional Space: An Acceleration Technique for Particle Swarm Optimization
Feng Wu, Yuelin Zhao, Jianhua Pang +2
Compared with random sampling, low-discrepancy sampling is more effective in covering the search space. However, the existing research cannot definitely state whether the impact of…
Two Iterative algorithms for the matrix sign function based on the adaptive filtering technology
Feng Wu, Keqi Ye, Li Zhu +3
In this paper, two new efficient algorithms for calculating the sign function of the large-scale sparse matrix are proposed by combining filtering algorithm with Newton method and…
Updating velocities in heterogeneous comprehensive learning particle swarm optimization with low-discrepancy sequences
Yuelin Zhao, Feng Wu, Jianhua Pang +1
Heterogeneous comprehensive learning particle swarm optimization (HCLPSO) is a type of evolutionary algorithm with enhanced exploration and exploitation capabilities. The low-discr…
A new stable and avoiding inversion iteration for computing matrix square root
Li Zhu, Keqi Ye, Yuelin Zhao +3
The objective of this research was to compute the principal matrix square root with sparse approximation. A new stable iterative scheme avoiding fully matrix inversion (SIAI) is pr…