Open AccessThe Sufficient Descent Condition of Nonlinear Conjugate Gradient Method
Author(s) -
Srimazzura Basri,
Mustafa Mamat,
Puspa Liza Ghazali
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.30.22367
Subject(s) - conjugate gradient method , nonlinear conjugate gradient method , derivation of the conjugate gradient method , conjugate residual method , gradient descent , gradient method , conjugate , mathematics , descent (aeronautics) , nonlinear system , mathematical optimization , computer science , mathematical analysis , artificial neural network , physics , artificial intelligence , quantum mechanics , meteorology
Non-linear conjugate gradient methods has been widely used instrumental in solving large scale optimization. These methods has been proved that only required very low memory other than its numerical efficiency. Thus, many studies have been conducted to improve these methods to find the most efficient method. In this paper, we proposed a new non-linear conjugate gradient coefficient that guarantees sufficient descent condition. Numerical tests indicate that the proposed coefficient is better than the three classical conjugate gradient coefficients.