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DOI: 10.14569/IJARAI.2016.050303
PDF

Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules

Author 1: Nagy Ramadan Darwish
Author 2: Ahmed A. Mohamed
Author 3: Bassem S. M. Zohdy

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 5 Issue 3, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: This research aims to calculate the execution time for software modules, using Particle Swarm Optimization (PSO) and Parallel Particle Swarm Optimization (PPSO), in order to calculate the proper time. A comparison is made between MATLAB Code without Algorithm (MCWA), PSO and PPSO to figure out the time produced when executing any software module. The proposed algorithms which include the PPSO increase the speed of executing the algorithm itself, in order to achieve quick results. This research introduces the proposed architecture to calculate execution time and uses MATLAB to implement MCWA, PSO and PPSO. The results show that PPSO algorithm is more efficient in speed and time compared to MCWA and PSO algorithm for calculating the execution time.

Keywords: Particle Swarm Optimization; Parallel Particle Swarm Optimization; MATLAB Code without Algorithm

Nagy Ramadan Darwish, Ahmed A. Mohamed and Bassem S. M. Zohdy, “Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 5(3), 2016. http://dx.doi.org/10.14569/IJARAI.2016.050303

@article{Darwish2016,
title = {Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2016.050303},
url = {http://dx.doi.org/10.14569/IJARAI.2016.050303},
year = {2016},
publisher = {The Science and Information Organization},
volume = {5},
number = {3},
author = {Nagy Ramadan Darwish and Ahmed A. Mohamed and Bassem S. M. Zohdy}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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