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  1. 1
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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  2. 2
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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  3. 3
    A random search based effective algorithm for pairwise test data generation

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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  4. 4
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
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  5. 5
    EasyA: Easy and effective way to generate pairwise test data

    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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  6. 6
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  8. 8
    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure

    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

    Published 2019
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  9. 9
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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  10. 10
    Some metaheuristic algorithms for solving multiple cross-functional team selection problems

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
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  11. 11
    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin

    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

    Published 2017
    “…Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. …”
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  12. 12
    Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction

    Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

    Published 2019
    “…Comparison of this framework continue in some of the state-of-the-arts algorithm in the literature and the results is outperformed based on the proposed algorithm experimental result.…”
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  13. 13
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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  14. 14
    Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms

    Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

    Published 2016
    “…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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  15. 15
    Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii

    Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii by Shafii, Muhammed Khaleeq

    Published 2012
    “…This project focuses on three main objectives to investigate the UPSR Examination of data for prediction result, to study the Clonal Selection algorithm of the term and to develop the Prediction of UPSR Result System using Clonal Selection Algorithm. …”
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  16. 16
    Weed recognition based on erosion and dilation segmentation algorithm

    Weed recognition based on erosion and dilation segmentation algorithm by S., Sulaiman, M.H., Siddiqi, I., Ahmad

    Published 2009
    “…In this paper an algorithm is developed for automatic spray control system. …”
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  17. 17
    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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  18. 18
    Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences

    Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

    Published 2024
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  19. 19
    Performance of various training algorithms on scene illumination classification

    Performance of various training algorithms on scene illumination classification by Hesamian, Mohammad Hesam, Mashohor, Syamsiah, Saripan, M. Iqbal, Wan Adnan, Wan Azizun, Hesamian, B., Hooshyari, M. M.

    Published 2015
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  20. 20
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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