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  1. 1

    Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing by S. Ahmed, Bestoun

    Published 2011
    “…Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. …”
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    Thesis
  2. 2

    Verification of correctness properties for aggregation behavior of swarm robotics system using spin model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

    Published 2015
    “…This algorithm is based on PFSA only relies on local interactions between individuals, the extensibility of the algorithm is very weak. …”
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    Thesis
  3. 3
  4. 4

    Verification correctness properties for aggregation behavior of swarm robotics system using SPIN model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

    Published 2015
    “…This algorithm is based on PFSA only relies on local interactions between individuals, the extensibility of the algorithm is very weak. …”
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    Thesis
  5. 5

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…Artificial neuro-glial networks is proposed to be combined in the swarm-based communication algorithm to provide a human-like model for the robot's communication and optimization.…”
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    Monograph
  6. 6

    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

    Published 2019
    “…The reason is that the T-way sequence input interaction is NP-Hard problem. In this research, Fish Swarm algorithm is proposed to adapt with T-way sequence input interaction test strategy. …”
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    Conference or Workshop Item
  7. 7

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…In this paper, a new balancing mechanism based on multi-swarm approach is proposed for balancing exploration and exploitation in metaheuristics. …”
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    Article
  8. 8

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Article
  9. 9

    A microscopic swarm model simulation and fractal approach towards swarm agent behaviour by Widyarto, Setyawan, Abd. Latiff, Muhammad Shafie

    Published 2006
    “…The developed model also uses the physical based variables that can be measured. The collision avoidance algorithm is influenced by existing algorithm flock which uses the steering behaviour to animate birds. …”
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    Article
  10. 10

    Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Al-Khateeb, Bellal, Mohamad Fadli, Zolkipli

    Published 2019
    “…Most of these algorithms were inspired either by nature or the behavior of certain swarms, such as birds, ants, bees, or even bats. …”
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    Book Chapter
  11. 11

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…The performance of SMOPE and SMOPE-MS has been examined through the utilization of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). …”
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    Article
  12. 12
  13. 13

    Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

    Published 2018
    “…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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    Book Chapter
  14. 14

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
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    Thesis
  15. 15

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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    Article
  16. 16

    Correlation with the fundamental PSO and PSO modifications to be hybrid swarm optimization by Hasan, Raed A, Najim, Suhel Shahab, Ahmed, Munef Abdullah

    Published 2021
    “…Swarm-based metaheuristics, including nature-inspired populace-based methods, have been developed to aid the creation of quick, robust, and low-cost solutions for complex problems. …”
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    Article
  17. 17

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…The temporal properties of the video sequences undergo computation across full corresponding blocks frames to give motion based information. The features are reduced using the particle swarm optimization detection technique in video image sequences to reduce the computational complexity. …”
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    Article
  18. 18

    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

    Published 2018
    “…In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). …”
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    Article
  19. 19

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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    Thesis
  20. 20

    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2019
    “…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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    Article