| _version_ |
1860799677645979648
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2019-12-04 02:49:46
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| eventvenue |
Bali, Indonesia
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| format |
Restricted Document
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| id |
6962
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| institution |
UniSZA
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| originalfilename |
2012-01-FH03-FIK-19-35707.pdf
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| person |
Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML
like Gecko) Chrome/78.0.3904.108 Safari/537.36
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6962
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| spelling |
6962 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6962 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 5 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/78.0.3904.108 Safari/537.36 2019-12-04 02:49:46 2012-01-FH03-FIK-19-35707.pdf UniSZA Private Access New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search Hybrid conjugate gradient (CG) techniques are one of the most prominent procedure for obtaining the solution of large-scale unconstrained optimization problems. This is due to its simplicity, global convergence, and low memory requirement. Numerous modifications have been done recently to improve the performance of these methods. In this paper, we proposed new class of hybrid CG coefficients with guaranteed descent under exact line search. Numerical results are presented to illustrate the efficiency of the proposed methodscompared to other classical CG coefficients. 7th International Conference on Global Optimization and Its Application 2018 Bali, Indonesia
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| spellingShingle |
New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
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| summary |
Hybrid conjugate gradient (CG) techniques are one of the most prominent procedure for obtaining the solution of large-scale unconstrained optimization problems. This is due to its simplicity, global convergence, and low memory requirement. Numerous modifications have been done recently to improve the performance of these methods. In this paper, we proposed new class of hybrid CG coefficients with guaranteed descent under exact line search. Numerical results are presented to illustrate the efficiency of the proposed methodscompared to other classical CG coefficients.
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| title |
New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
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| title_full |
New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
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| title_fullStr |
New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
|
| title_full_unstemmed |
New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
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| title_short |
New class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
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| title_sort |
new class of hybrid conjugate gradient coefficients with guaranteed descent and efficient line search
|