The performance analysis of a new modification of conjugate gradient parameter for unconstrained optimization models
Abstract
Conjugate Gradient (CG) method is the most prominent iterative mathematical technique that can be useful for the optimization of both linear and non-linear systems due to its simplicity, low memory requirement, computational cost, and global convergence properties. However, some of the classical CG methods have some drawbacks which include weak global convergence, poor numerical performance both in terms of number of iterations and the CPU time....
Paper Details
Title
The performance analysis of a new modification of conjugate gradient parameter for unconstrained optimization models
Published Date
Jan 1, 2021
Journal
Volume
9
Issue
1
Pages
16 - 23
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History