Jafar Gholami
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Jafar Gholami has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Hossam M. Zawbaa
Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt
3 shared publications Somayeh Mohammadi
Department of Computer Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
2 shared publicationsElahe Hosseinkhani
Department of Computer Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
1 shared publication- Farhad Mardukhi
Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran
1 shared publication - Farhad Pourpanah
Department of Electrical and Computer Engineering, Queens University, Kingston, Canada
1 shared publication Fariba Abbasi Nia
Department of Computer Engineering, Kermanshah Science and Research Branch, Islamic Azad University, Kermanshah, Iran
1 shared publication
Latest Publications
- 24 April 2023
- Published by Springer Nature in Soft Computing
- Vol. 27 (14) , 9673-9691
Effective hybridization of JAYA and teaching–learning-based optimization algorithms for numerical function optimization
- 24 April 2023
- Published by Springer Nature in Soft Computing
- Vol. 27 (14) , 9673-9691
Effective hybridization of JAYA and teaching–learning-based optimization algorithms for numerical function optimization
- 14 March 2022
- Published by Springer Nature in Soft Computing
- Vol. 26 (11) , 5315-5333
Powerful enhanced Jaya algorithm for efficiently optimizing numerical and engineering problems
- 14 March 2022
- Published by Springer Nature in Soft Computing
- Vol. 26 (11) , 5315-5333
Powerful enhanced Jaya algorithm for efficiently optimizing numerical and engineering problems
- 3 September 2021
- Published by Springer Nature in Soft Computing
- Vol. 25 (22) , 14393-14411
An intelligent hybrid JAYA and crow search algorithms for optimizing constrained and unconstrained problems
- 3 September 2021
- Published by Springer Nature in Soft Computing
- Vol. 25 (22) , 14393-14411
An intelligent hybrid JAYA and crow search algorithms for optimizing constrained and unconstrained problems
- 3 May 2021
- Published by Springer Nature in Soft Computing
- Vol. 25 (14) , 9441-9454
An improved crow search algorithm for solving numerical optimization functions
- 3 May 2021
- Published by Springer Nature in Soft Computing
- Vol. 25 (14) , 9441-9454
An improved crow search algorithm for solving numerical optimization functions
- 30 September 2020
- Published by Springer Nature in Soft Computing
- Vol. 25 (4) , 2837-2849
A novel global harmony search algorithm for solving numerical optimizations
- 30 September 2020
- Published by Springer Nature in Soft Computing
- Vol. 25 (4) , 2837-2849
A novel global harmony search algorithm for solving numerical optimizations
- 1 August 2020
- Published by Elsevier in Applied Soft Computing
- Vol. 93
Feature selection based on improved binary global harmony search for data classification
- 1 August 2020
- Published by Elsevier in Applied Soft Computing
- Vol. 93
Feature selection based on improved binary global harmony search for data classification
- 1 October 2018
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 40-46
A Novel Combination of Bees and Firefly Algorithm to Optimize Continuous Problems
Although Bees algorithm (BA) has presented great performance so far in optimizing different problems, it still has weak convergence rate in some optimizations. Therefore, in this investigation in order to resolve its weakness and boost the exploitation of algorithm, it was hybridized by Firefly algorithm (FA). The hybrid bees and firefly algorithm (BA-FA) was implemented on twelve numerical benchmark functions to evaluate it. The BA-FA was also compared with four famous algorithms, including particle swarm optimization (PSO), invasive weed optimization (IWO) and so on. The results showed that BA-FA had the best performance and convergence in optimizing the mentioned functions.
- 1 October 2018
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 40-46
A Novel Combination of Bees and Firefly Algorithm to Optimize Continuous Problems
Although Bees algorithm (BA) has presented great performance so far in optimizing different problems, it still has weak convergence rate in some optimizations. Therefore, in this investigation in order to resolve its weakness and boost the exploitation of algorithm, it was hybridized by Firefly algorithm (FA). The hybrid bees and firefly algorithm (BA-FA) was implemented on twelve numerical benchmark functions to evaluate it. The BA-FA was also compared with four famous algorithms, including particle swarm optimization (PSO), invasive weed optimization (IWO) and so on. The results showed that BA-FA had the best performance and convergence in optimizing the mentioned functions.