无约束优化共轭梯度法参数的上尺度化

IF 1.1 Q1 MATHEMATICS
Basim A. Hassan, Hawraz N. Jabbar, Yoksal A. Laylani
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引用次数: 0

摘要

共轭梯度算法是一种基于共轭梯度参数的有效迭代技术。通过满足共轭性要求,可以利用二阶泰勒级数构造有效的参数共轭梯度。在分析了新算法的收敛特性后,给出了一些数值结果,证明了改进方法的鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Upscaling parameters for conjugate gradient method in unconstrained optimization
An effective iterative technique, conjugate gradient algorithm is based on the conjugate gradient parameters. By satisfying the conjugacy requirement, one may construct an effective parameters conjugate gradient using a second order Taylor series. After an analysis of the new algorithm’s convergence characteristics, we provide some numerical findings that demonstrate the robustness and effectiveness of the improved methods.
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来源期刊
CiteScore
2.70
自引率
23.50%
发文量
141
期刊介绍: The Journal of Interdisciplinary Mathematics (JIM) is a world leading journal publishing high quality, rigorously peer-reviewed original research in mathematical applications to different disciplines, and to the methodological and theoretical role of mathematics in underpinning all scientific disciplines. The scope is intentionally broad, but papers must make a novel contribution to the fields covered in order to be considered for publication. Topics include, but are not limited, to the following: • Interface of Mathematics with other Disciplines • Theoretical Role of Mathematics • Methodological Role of Mathematics • Interface of Statistics with other Disciplines • Cognitive Sciences • Applications of Mathematics • Industrial Mathematics • Dynamical Systems • Mathematical Biology • Fuzzy Mathematics The journal considers original research articles, survey articles, and book reviews for publication. Responses to articles and correspondence will also be considered at the Editor-in-Chief’s discretion. Special issue proposals in cutting-edge and timely areas of research in interdisciplinary mathematical research are encouraged – please contact the Editor-in-Chief in the first instance.
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