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  1. 1

    A variable combinatorial test suite strategy based on modified greedy algorithm by Homaid, Ameen A. Ba, Alsewari, Abdulrahman A.

    Published 2015
    “…A variable strength interaction is the interaction between some of software features which have higher priority than the interaction between the others software features. …”
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    Conference or Workshop Item
  2. 2

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

    Published 2011
    “…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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    Thesis
  3. 3

    Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Zamli, Kamal Z., Alsariera, Yazan A.

    Published 2018
    “…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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    Article
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    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
    Conference paper
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    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…This, however, leads to sub-optimality of prediction accuracy as the orthogonal array design lacks in offering higher-order variable interactions, in addition to its fixed and limited variable combinations to be assessed and evaluated. …”
    Article
  8. 8

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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    Article
  9. 9

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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    Article
  10. 10

    A Two Pressure-Velocity Approach for Immersed Boundary Methods in Three Dimensional Incompressible Flows by Tuan Mohammad Yusoff, Tuan Ya, Sabir, O., Norhafizan, Ahmed, Y., Nukman

    Published 2013
    “…The algorithm calculates the interactions between incompressible viscous flows and a solid shape in three-dimensional domain. …”
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    Conference or Workshop Item
  11. 11

    Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing by Muazu, Aminu Aminu, Hashim, Ahmad Sobri

    Published 2025
    “…The Harmony Search (HS) algorithm is a recent metaheuristic that mimics musicians’ improvisation to create pleasant compositions according to aesthetic standards widely used in different areas continuously adjusts solution variables to find the best outcome. …”
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    Article
  12. 12

    Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

    Published 2020
    “…The proposed feature selection technique comprises of Multi-objective Binary-valued Backtracking Search Algorithm (MOBBSA). It is used to search within a number of input variables combinations and to select the feature subsets, which minimizes simultaneously vice-versa the estimation error and the feature numbers. …”
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  13. 13

    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

    Published 2020
    “…Besides, in the existing NEPID controller structure of the SISO system, only a single node of hormone regulation is used due to a single control variable. Meanwhile, in the MIMO systems, many control variables available that interact with each other, and the single node hormone regulation of NEPID is still inadequate in producing better control accuracy of nonlinear MIMO systems. …”
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  14. 14

    A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling by Purnomo, Muhammad Ridwan Andi, Abdul Wahab, Dzuraidah, Hassan, Azmi, Rahmat, Riza Atiq

    Published 2009
    “…Since the car interact with each other on the road and the driver progressive level is different, three interaction variables, that are current car speed, distance to the car ahead and driver progressive level, are defined and an indication of their influence on the tire-road slippage index is analysed. …”
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    Article
  15. 15

    A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia by Lim, San Yee

    Published 2018
    “…The behaviors and interactions among the stocks in Bursa Malaysia are then determined by using the Forest of all possible minimum spanning trees. …”
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    How social media crisis response and social interaction is helping people recover from Covid-19: an empirical investigation by Bukar, Umar Ali, A. Jabar, Marzanah, Sidi, Fatimah, Nor, R. N. H., Abdullah, Salfarina, Ishak, Iskandar

    Published 2022
    “…The result shows that all the variables are useful and reveal good performance. Thus, crisis management and communication activities should pay more attention to these variables for effective social media crisis communication. …”
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  19. 19

    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. …”
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  20. 20

    Survey on input output relation based combination test data generation strategies by Alsewari, Abdulrahman A., Tairan, Nasser M., Kamal Z., Zamli

    Published 2015
    “…Combinatorial test data generation strategies have been known to be effective to detect the fault in the product due to the interaction between the product’s features. Over the years, many combinatorial test data generation strategies have been developed supporting uniform and variable strength interactions. …”
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    Article