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Global Convergence of a New Coefficient Nonlinear Conjugate Gradient Method

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dc.contributor.author Nur Syarafina Mohamed
dc.contributor.author Mustafa Mamat
dc.contributor.author Mohd Rivaie
dc.contributor.author Shazlyn Milleana Shaharuddin.
dc.contributor.author (UniKL MITEC)
dc.date.accessioned 2018-05-08T08:01:20Z
dc.date.available 2018-05-08T08:01:20Z
dc.date.issued 2018-05-08
dc.identifier.other Indonesian Journal of Electrical Engineering and Computer Science
dc.identifier.uri http://ir.unikl.edu.my/jspui/handle/123456789/18895
dc.description Venue: Avillion Legacy Melaka en_US
dc.description.abstract Nonlinear conjugate gradient (CG) methods are widely used in optimization field due to its efficiency for solving a large scale unconstrained optimization problems. Many studies and modifications have been developed in order to improve the method. The method is known to possess sufficient descend condition and its global convergence properties under strong Wolfe-Powell search direction. In this paper, the new coefficient of CG method is presented. The global convergence and sufficient descend properties of the new coefficient are established by using strong Wolfe-Powell line search direction. Results show that the new coefficient is able to globally converge under certain assumptions and theories. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Vol. 5, No. 3, March 2017, pp. 401 ~ 408;
dc.subject Conjugate Gradient Method en_US
dc.subject Strong Wolfe-Powell Line search en_US
dc.subject Global convergence en_US
dc.title Global Convergence of a New Coefficient Nonlinear Conjugate Gradient Method en_US
dc.conference.name INTERNATIONAL CONFERENCE ON ADVANCEMENT IN COMPUTING AND INFORMATION SYSTEM (KADCIS 2018) en_US
dc.conference.year 2018 en_US


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