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Al-Naemi, Gh.M. and Ahmed, H.I. (2013) Modified Nonlinear Conjugate Gradient Algorithms with Application in Neural Networks. LAP Lambert Academic Publishing, Saarbrucken.

has been cited by the following article:

• TITLE: Global Convergence Property with Inexact Line Search for a New Hybrid Conjugate Gradient Method

  AUTHORS: Fanar N. Al-Namat, Ghada M. Al-Naemi

  KEYWORDS: Unconstrained Optimization, Hybrid, Conjugate Gradient

  JOURNAL NAME: Open Access Library Journal, Vol.7 No.2, February 11, 2020

  ABSTRACT: In this study, we derive a new scale parameter φ for the CG method, for solving large scale unconstrained optimization algorithms. The new scale parameter φ satisfies the sufficient descent condition, global convergence analysis proved under Strong Wolfe line search conditions. Our numerical results show that the proposed method is effective and robust against some known algorithms.