New conjugacy condition with pair-conjugate gradient methods for unconstrained optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2009 Conjugate gradient methods are wildly used for unconstrained optimization especially when the dimension is large. In this paper we propose a new kind of nonlinear conjugate gradient methods which on the study of Dai and Liao (2001), the new idea is how ...
Abbas Al-Bayati, Huda Ahmed
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Journal of Computational and Applied Mathematics, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiao Liang Dong +3 more
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New conjugacy condition and related new conjugate gradient methods for unconstrained optimization
Journal of Computational and Applied Mathematics, 2007 The authors study the conjugate gradient method for solving large-scale nonlinear optimization problems. In the first two sections, the authors present the necessary background relating to conjugate methods in general and choices for the conjugacy condition.
Li, Guoyin, Tang, Chunming, Wei, Zengxin
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Four–Term Conjugate Gradient (CG) Method Based on Pure Conjugacy Condition for Unconstrained Optimization [PDF]
Kirkuk Journal of Science, 2018 A four-term CG-method based on pure conjugacy condition are proposed, Research activities on extending three-term CG-method to the four-term conjugate gradient method.
Hisham. M. Azzam +2 more
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A New Conjugate Gradient Algorithms Using Conjugacy Condition for solving unconstrained optimization
Indonesian Journal of Electrical Engineering and Computer Science, 2021 The primarily objective of this paper which is indicated in the field of conjugate gradient algorithms for unconstrained optimization problems and algorithms is to show the advantage of the new proposed algorithm in comparison with the standard method which is denoted as.
Aseel M. Qasim +2 more
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A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method [PDF]
Mathematical Problems in Engineering, 2014 The conjugate gradient (CG) method has played a special role in solving large‐scale nonlinear optimization problems due to the simplicity of their very low memory requirements. In this paper, we propose a new conjugacy condition which is similar to Dai‐Liao (2001). Based on this condition, the related nonlinear conjugate gradient method is given.
Shengwei Yao, Xiwen Lu, Bin Qin
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New Scaled Conjugate Gradient Algorithm for Training Artificial Neural Networks Based on Pure Conjugacy Condition [PDF]
Kirkuk Journal of Science, 2015 Conjugate gradient methods constitute excellent neural network training methods characterized by their simplicity efficiency and their very low memory requirements.
Khalil K. Abbo, Hind H. Mohamed
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A Hybrid Conjugate Gradient Algorithm for Nonlinear System of Equations through Conjugacy Condition
Artificial Intelligence and Applications, 2023 the purpose of solving a large-scale system of nonlinear equations, a hybrid conjugate gradient algorithm is introduced in thispaper, based on the convex combination ofβFRkandβPRPkparameters. It is made possible by incorporating the conjugacy condition togetherwith the proposed conjugate gradient search direction. Furthermore, a significant property of
Aliyu Yusuf +2 more
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A spectral Fletcher-Reeves conjugate gradient method with integrated strategy for unconstrained optimization and portfolio selection. [PDF]
PLoS ONEThe spectral conjugate gradient (SCG) technique is highly efficient in addressing large-scale unconstrained optimization challenges. This paper presents a structured SCG approach that combines the Quasi-Newton direction and an extended conjugacy ...
Nasiru Salihu +4 more
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On transitive permutation groups with a subgroup satisfying a certain conjugacy condition
Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics, 1984 AbstractLet G be transitive permutation group of degree n and let K be a nontrivial pronormal subgroup of G (that is, for all g in G, K and Kg are conjugate in (K, Kg)). It is shown that K can fix at most ½(n – 1) points. Moreover if K fixes exactly ½(n – 1) points then G is either An or Sn, or GL(d, 2) in its natural representation where n = 2d-1 ≥ 7.
C. Praeger
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