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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Basim Abbas Hassan
University of Mosul

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

 1 
A new class of BFGS updating formula based on the new quasi-newton equation Basim Abbas Hassan; Hussein K. Khalo
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp945-953

Abstract

Quasi-Newton methods” are amongst the mainly useful and competent iterative process for solving unrestrained minimization functions. In this paper we derive a new quasi-Newton equation with on the Hessian estimate updates and alterations intended at developing their performance. The “Numerical results” illustrate that the proposed technique useful for the known test functions.
A new formula for conjugate parameter computation based on the quadratic model Basim Abbas Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp954-961

Abstract

The conjugancy coefficient is the very basis of a diversity of the conjugate gradient methods. In this research, we derivation a new formula of conjugate gradient methods based on the quadratic model. Our arithmetical findings have revealed that, our new method has the most excellent performance contrast to the other standard CG methods. Also give proof viewing that this method converges globally.
A new variants of quasi-newton equation based on the quadratic function for unconstrained optimization Basim Abbas Hassan; Mohammed W. Taha
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp701-708

Abstract

The focus for quasi-Newton methods is the quasi-Newton equation. A new quasi-Newton equation is derived for quadratic function. Then, based on this new quasi-Newton equation, a new quasi-Newton updating formulas are presented. Under appropriate conditions, it is shown that the proposed method is globally convergent. Finally, some numerical experiments are reported which verifies the effectiveness of the new method.
A new kind of parameter conjugate gradient for unconstrained optimization Basim Abbas Hassan; Hussein O. Dahawi; Azzam S. Younus
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp404-411

Abstract

In this paper, a replacement new parameter conjugate gradient  for unconstrained optimization. The sufficient descent property cleave to. The global convergence property of the new method is proved under some assumptions. Numerical results explain that the  new parameter is superior  in practice. 
A variant of hybrid conjugate gradient methods based on the convex combination for optimization Basim Abbas Hassan; Ahmed Obeid Owaid; Zena T. Yasen
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp1007-1015

Abstract

On some studies a conjugate parameter plays an important role for the conjugate gradient methods. In this paper, a variant of hybrid is provided in the search direction based on the convex combination. This search direction ensures that the descent condition holds. The global convergence of the variant of hybrid is also obtained. Our strong evidence is a numerical analysis showing that the proposed variant of hybrid method is efficient than the Hestenes and Stiefel method. 
A new quasi-newton equation on the gradient methods for optimization minimization problem Basim Abbas Hassan; Ghada M. Al-Naemi
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp737-744

Abstract

The quasi-Newton equation is the very foundation of an assortment of the quasi-Newton methods for optimization minimization problem. In this paper, we deriving a new quasi-Newton equation based on the second-order Taylor’s series expansion. The global convergence is established underneath suitable conditions and numerical results are reported to show that the given algorithm is more effective than those of the normal BFGS method.
An improved quasi-Newton equation on the quasi-Newton methods for unconstrained optimizations Basim Abbas Hassan; Kanikar Muangchoo; Fadhil Alfarag; Abdulkarim Hassan Ibrahim; Auwal Bala Abubakar
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp997-1005

Abstract

Quasi-Newton methods are a class of numerical methods for solving the problem of unconstrained optimization. To improve the overall efficiency of resulting algorithms, we use the quasi-Newton methods which is interesting for quasi-Newton equation. In this manuscript, we present a modified BFGS update formula based on the new quasi-Newton equation, which give a new search direction for solving unconstrained optimizations proplems. We analyse the convergence rate of quasi-Newton method under some mild condition. Numerical experiments are conducted to demonstrate the efficiency of new methods using some test problems. The results indicates that the proposed method is competitive compared to the BFGS methods as it yielded fewer iteration and fewer function evaluations.
Co-Authors Abdulkarim Hassan Ibrahim Ahmed Obeid Owaid Auwal Bala Abubakar Azzam S. Younus Fadhil Alfarag Ghada M. Al-Naemi Hussein K. Khalo Hussein O. Dahawi Kanikar Muangchoo Mohammed W. Taha Zena T. Yasen