JOURNAL ARTICLE
Development a Special Conjugate Gradient Algorithm for Solving Unconstrained Minimization Problems
Year: 2012 Journal: Maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/Al-Rafidain journal for computer sciences and mathematics Vol: 9 (1)Pages: 73-84
Abstract
This paper develops a special conjugate gradient algorithm for solving unconstrained minimized problems. This development can be regarded as some kind of convex combination of the MPR and MLS methods. Experimental results indicate that the new algorithm is more efficient than the Polak and Ribiere - algorithm.
Keywords:
Conjugate gradient method Algorithm Minification Gradient method Nonlinear conjugate gradient method Conjugate Computer science Derivation of the conjugate gradient method Conjugate residual method Mathematical optimization Mathematics Gradient descent Artificial intelligence Artificial neural network
Metrics
8
Cited By
0.00
FWCI (Field Weighted Citation Impact)
6
Refs
0.38
Citation Normalized Percentile
Is in top 1%
Is in top 10%
Citation History
Topics
Advanced Optimization Algorithms Research
Physical Sciences → Mathematics → Numerical Analysis
Statistical and numerical algorithms
Physical Sciences → Mathematics → Applied Mathematics
Matrix Theory and Algorithms
Physical Sciences → Computer Science → Computational Theory and Mathematics
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