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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  3. 3
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  4. 4
    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation

    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…This thesis aims to solve these problems using an efficient metaheuristic algorithm, known as the Harmony Search (HS) algorithm. …”
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  5. 5
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  6. 6
    Automatic clustering of gene ontology by genetic algorithm

    Automatic clustering of gene ontology by genetic algorithm by Othman, Razib M., Deris, Safaai, Zakaria, Zalmiyah, Illias, Rosli M., Mohamad, Saberi M.

    Published 2006
    “…Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. …”
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  7. 7
    An adaptive density-based method for clustering evolving data streams / Amineh Amini

    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…However, existing density-based data stream clustering algorithms are not without problems. The first problem refers to the high computation time required for the clustering process. …”
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  8. 8
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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  9. 9
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…For the third problem a modified of Kohonen Network (MKN) algorithm was proposed to select the initial centres of clusters. …”
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  10. 10
    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman

    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…These conditions have led the existing partitional algorithms to local minima and empty clusters problems. …”
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  11. 11
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Genetic algorithms are well known methods with high ability to resolve optimization problems including clustering. …”
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  12. 12
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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  13. 13
    Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz

    Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz by Aziz, Azwani

    Published 2010
    “…There are many techniques of clustering the image. The most widely used of clustering technique is Fuzzy C-Means algorithm (FCM). …”
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  14. 14
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. …”
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  15. 15
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. …”
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  16. 16
    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

    Published 2012
    “…The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. …”
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  17. 17
    Improved clustering using robust and classical principal component

    Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

    Published 2017
    “…To remedy this problem, we propose to integrate Principal Component analysis (PCA) which is useful for dimensionality reduction of a dataset with the k-means clustering algorithm. …”
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  18. 18
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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  19. 19
    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…These problems can be addressed by the Multi-Objective Particle Swarm Optimization (MOPSO) approach, which is commonly used in addressing optimization problems. …”
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  20. 20
    A review: accuracy optimization in clustering ensembles using genetic algorithms

    A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

    Published 2011
    “…Genetic algorithms are known as methods with high ability to solve optimization problems including clustering. …”
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