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1860799641123028992
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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 |
2016-09-14 11:15:34
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| eventvenue |
Kuala Lumpur, Malaysia
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| format |
Restricted Document
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| id |
6807
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| institution |
UniSZA
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| originalfilename |
1109-01-FH03-FIK-16-06517.jpg
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| person |
norman
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6807
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| spelling |
6807 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6807 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper image/jpeg inches 96 96 norman 769 2016-09-14 11:15:34 1428x769 1428 44 44 1109-01-FH03-FIK-16-06517.jpg UniSZA Private Access A modified form of conjugate gradient method for unconstrained optimization problems Conjugate gradient (CG) methods have been recognized as an interesting technique to solve optimization problems, due to the numerical efficiency, simplicity and low memory requirements. In this paper, we propose a new CG method based on the study of Rivaie et al. [7] (Comparative study of conjugate gradient coefficient for unconstrained Optimization, Aus. J. Bas. Appl. Sci. 5(2011) 947-951). Then, we show that our method satisfies sufficient descent condition and converges globally with exact line search. Numerical results show that our proposed method is efficient for given standard test problems, compare to other existing CG methods. 2nd International Conference on Mathematical Sciences and Statistics: Innovations Through Mathematical and Statistical Research, ICMSS 2016 Kuala Lumpur, Malaysia
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| spellingShingle |
A modified form of conjugate gradient method for unconstrained optimization problems
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| summary |
Conjugate gradient (CG) methods have been recognized as an interesting technique to solve optimization problems, due to the numerical efficiency, simplicity and low memory requirements. In this paper, we propose a new CG method based on the study of Rivaie et al. [7] (Comparative study of conjugate gradient coefficient for unconstrained Optimization, Aus. J. Bas. Appl. Sci. 5(2011) 947-951). Then, we show that our method satisfies sufficient descent condition and converges globally with exact line search. Numerical results show that our proposed method is efficient for given standard test problems, compare to other existing CG methods.
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| title |
A modified form of conjugate gradient method for unconstrained optimization problems
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| title_full |
A modified form of conjugate gradient method for unconstrained optimization problems
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| title_fullStr |
A modified form of conjugate gradient method for unconstrained optimization problems
|
| title_full_unstemmed |
A modified form of conjugate gradient method for unconstrained optimization problems
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| title_short |
A modified form of conjugate gradient method for unconstrained optimization problems
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| title_sort |
modified form of conjugate gradient method for unconstrained optimization problems
|