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  1. 1

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machine (SVM) is a present day classification approach originated from statistical approaches.Two main problems that influence the performance of SVM are selecting feature subset and SVM model selection. …”
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  2. 2

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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  3. 3

    Enhanced selection method for genetic algorithm to solve traveling salesman problem by Jubeir, Mohammed, Almazrooie, Mishal, Abdullah, Rosni

    Published 2017
    “…Genetic algorithms (GAs) have been applied by many researchers to get an optimized solution for hard problems such as Traveling Salesman Problem (TSP). …”
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    Conference or Workshop Item
  4. 4

    Integrated ACOR/IACOMV-R-SVM Algorithm by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…The main problems of SVM are selecting feature subset and tuning the parameters. …”
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  5. 5

    Genetic Algorithm Performance with Different Selection Strategies in Solving TSP by Noraini, Mohd Razali, Geraghty, John

    Published 2011
    “…There are several ways for selection. This paper presents the comparison of GA performance in solving travelling salesman problem (TSP) using different parent selection strategy. …”
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    Conference or Workshop Item
  6. 6

    Load flow method using genetic algorithm by Lok, C. W., Zin, A. A. M., Mustafa, M. W., Lo, Kueiming Lun

    Published 2003
    “…This paper presents the implemention of the simple genetic algorithm and constrained genetic algorithm to solve the load flow problem. …”
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  7. 7

    A prototype for driving school instructor timetabling using case-based heuristics selection algorithm / CT Munnirah Niesha Mohd Shafee by Mohd Shafee, CT Munnirah Niesha

    Published 2010
    “…Timetabling problems are present in all type of environment. This project is concern with problem constructing timetable for driving school instructor. …”
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    Thesis
  8. 8

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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    Thesis
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    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…We reviewed 57 SKF papers. 16 of them on fundamental improvements, 9 on extension of the algorithm to discrete problems and 25 on their applications. …”
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    Conference or Workshop Item
  12. 12

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…This thesis presents works on swarm intelligence algorithms that are inspired by real echolocation of a colony of bats and its performance evaluation to solve optimisation problems. …”
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    Thesis
  13. 13

    Metric's thresholds for encoding evolutionary computing representation in software engineering problem by Md Sultan, Abu Bakar, Din, Jamilah, Zulzalil, Hazura, Bakar, Abubakar Diwani

    Published 2015
    “…Algorithm was tested to metric selection problem using Genetic Algorithm and the results obtained are promising.…”
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    Article
  14. 14

    The effect of GA parameters on the performance of GA-based QoS routing algorithm by Yussof S., See O.H.

    Published 2023
    “…Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. …”
    Conference paper
  15. 15

    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…Therefore, this study addresses these problems by introducing a hybrid algorithm for MD. …”
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    Book Section
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    Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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    Article
  18. 18

    Comparison of swarm intelligence algorithms for high dimensional optimization problems by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2018
    “…Within a huge number of algorithms, selecting one algorithm among others for solving the high dimensional optimization problem is not an easily accomplished task. …”
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  19. 19

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…However, SVM suffers two main problems which include feature subset selection and parameter tuning. …”
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    Thesis
  20. 20

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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