Norrlaili Shapiee | Universiti Sains Islam Malaysia (USIM) (original) (raw)

Papers by Norrlaili Shapiee

Research paper thumbnail of MATHEMATICAL APPLICATION IN DETERMINING QIBLA DIRECTION OF TAMHIDI CENTRE, UNIVERSITI SAINS ISLAM MALAYSIA (USIM) BY USING SPHERICAL TRIGONOMETRY

The direction of the Qibla is the direction of the city of Makkah which is one of the legal condi... more The direction of the Qibla is the direction of the city of Makkah which is one of the legal conditions for performing prayer. Spherical trigonometry a branch of Mathematics plays a critical role in determining the direction of Qibla. This paper presents a trigonometry formula to calculate the direction of Qibla at the Tamhidi Centre at Universiti Sains Islam Malaysia (USIM). The calculated value of the Qibla azimuth of Tamhidi Centre, USIM is 292 35 44.44  

Research paper thumbnail of A modification of conjugate gradient method with descent properties

Research paper thumbnail of The application of new conjugate gradient methods in estimating data

International Journal of Engineering & Technology, 2018

Many researchers are intended to improve the conjugate gradient (CG) methods as well as their app... more Many researchers are intended to improve the conjugate gradient (CG) methods as well as their applications in real life. Besides, CG become more interesting and useful in many disciplines and has important role for solving large-scale optimization problems. In this paper, three types of new CG coefficients are presented with application in estimating data. Numerical experiments show that the proposed methods have succeeded in solving problems under strong Wolfe Powell line search conditions.

Research paper thumbnail of A new family of conjugate gradient coefficient with application

International Journal of Engineering & Technology, 2018

Conjugate gradient (CG) methods are famous for their utilization in solving unconstrained optimiz... more Conjugate gradient (CG) methods are famous for their utilization in solving unconstrained optimization problems, particularly for large scale problems and have become more intriguing such as in engineering field. In this paper, we propose a new family of CG coefficient and apply in regression analysis. The global convergence is established by using exact and inexact line search. Numerical results are presented based on the number of iterations and CPU time. The findings show that our method is more efficient in comparison to some of the previous CG methods for a given standard test problems and successfully solve the real life problem.

Research paper thumbnail of A new simple conjugate gradient coefficient for unconstrained optimization

Applied Mathematical Sciences, 2015

Conjugate gradient (CG) methods are important in solving unconstrained optimization especially fo... more Conjugate gradient (CG) methods are important in solving unconstrained optimization especially for large-scale unconstrained optimization. In this paper, we proposed a new simple CG coefficient. The global convergence result is established by using exact line search. Numerical results based on number of iterations and CPU time. Numerical result shows that our method is efficient when compared to the other CG coefficients for a given standard test problems.

Research paper thumbnail of A new modification of Hestenes-Stiefel method with descent properties

Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to i... more Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to its low memory requirements and global convergence properties. Numerous researches has been done to proposed new CG coefficients and to improve the efficiency. In this paper, we proposed a new CG coefficient based on the original Hestenes-Steifel CG coefficient. The global convergence result is established using exact line search. Most of our numerical results show that our method is very efficient when compared to the early CG coefficients for a given standard test problems.

Research paper thumbnail of A new modification of Hestenes-Stiefel method with descent properties

Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to i... more Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to its low memory requirements and global convergence properties. Numerous researches has been done to proposed new CG coefficients and to improve the efficiency. In this paper, we proposed a new CG coefficient based on the original Hestenes-Steifel CG coefficient. The global convergence result is established using exact line search. Most of our numerical results show that our method is very efficient when compared to the early CG coefficients for a given standard test problems.

Research paper thumbnail of A new classical conjugate gradient coefficient with exact line search

AIP Conference Proceedings, 2016

Research paper thumbnail of MATHEMATICAL APPLICATION IN DETERMINING QIBLA DIRECTION OF TAMHIDI CENTRE, UNIVERSITI SAINS ISLAM MALAYSIA (USIM) BY USING SPHERICAL TRIGONOMETRY

The direction of the Qibla is the direction of the city of Makkah which is one of the legal condi... more The direction of the Qibla is the direction of the city of Makkah which is one of the legal conditions for performing prayer. Spherical trigonometry a branch of Mathematics plays a critical role in determining the direction of Qibla. This paper presents a trigonometry formula to calculate the direction of Qibla at the Tamhidi Centre at Universiti Sains Islam Malaysia (USIM). The calculated value of the Qibla azimuth of Tamhidi Centre, USIM is 292 35 44.44  

Research paper thumbnail of A modification of conjugate gradient method with descent properties

Research paper thumbnail of The application of new conjugate gradient methods in estimating data

International Journal of Engineering & Technology, 2018

Many researchers are intended to improve the conjugate gradient (CG) methods as well as their app... more Many researchers are intended to improve the conjugate gradient (CG) methods as well as their applications in real life. Besides, CG become more interesting and useful in many disciplines and has important role for solving large-scale optimization problems. In this paper, three types of new CG coefficients are presented with application in estimating data. Numerical experiments show that the proposed methods have succeeded in solving problems under strong Wolfe Powell line search conditions.

Research paper thumbnail of A new family of conjugate gradient coefficient with application

International Journal of Engineering & Technology, 2018

Conjugate gradient (CG) methods are famous for their utilization in solving unconstrained optimiz... more Conjugate gradient (CG) methods are famous for their utilization in solving unconstrained optimization problems, particularly for large scale problems and have become more intriguing such as in engineering field. In this paper, we propose a new family of CG coefficient and apply in regression analysis. The global convergence is established by using exact and inexact line search. Numerical results are presented based on the number of iterations and CPU time. The findings show that our method is more efficient in comparison to some of the previous CG methods for a given standard test problems and successfully solve the real life problem.

Research paper thumbnail of A new simple conjugate gradient coefficient for unconstrained optimization

Applied Mathematical Sciences, 2015

Conjugate gradient (CG) methods are important in solving unconstrained optimization especially fo... more Conjugate gradient (CG) methods are important in solving unconstrained optimization especially for large-scale unconstrained optimization. In this paper, we proposed a new simple CG coefficient. The global convergence result is established by using exact line search. Numerical results based on number of iterations and CPU time. Numerical result shows that our method is efficient when compared to the other CG coefficients for a given standard test problems.

Research paper thumbnail of A new modification of Hestenes-Stiefel method with descent properties

Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to i... more Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to its low memory requirements and global convergence properties. Numerous researches has been done to proposed new CG coefficients and to improve the efficiency. In this paper, we proposed a new CG coefficient based on the original Hestenes-Steifel CG coefficient. The global convergence result is established using exact line search. Most of our numerical results show that our method is very efficient when compared to the early CG coefficients for a given standard test problems.

Research paper thumbnail of A new modification of Hestenes-Stiefel method with descent properties

Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to i... more Conjugate gradient (CG) methods are important for large-scale unconstrained optimization due to its low memory requirements and global convergence properties. Numerous researches has been done to proposed new CG coefficients and to improve the efficiency. In this paper, we proposed a new CG coefficient based on the original Hestenes-Steifel CG coefficient. The global convergence result is established using exact line search. Most of our numerical results show that our method is very efficient when compared to the early CG coefficients for a given standard test problems.

Research paper thumbnail of A new classical conjugate gradient coefficient with exact line search

AIP Conference Proceedings, 2016