Two-versions of descent conjugate gradient methods for large-scale unconstrained optimization
The conjugate gradient methods are noted to be exceedingly valuable for solving large-scale unconstrained optimization problems since it needn't the storage of matrices. Mostly the parameter conjugate is the focus for conjugate gradient methods. The current paper proposes new methods of paramet...
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| Main Authors: | , |
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| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2021-06-01.
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| Subjects: | |
| Online Access: | Get fulltext |
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |