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  1. 1
    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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  2. 2
    Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking

    Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

    Published 2024
    “…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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  3. 3
    Path optimization using genetic algorithm evolution

    Path optimization using genetic algorithm evolution by Low C.Y., Chong K.H., Salleh K., Johnny K.S.P.

    Published 2023
    Conference paper
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  4. 4
    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim

    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

    Published 2007
    “…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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  5. 5
    Differential evolution optimization for constrained routing in Wireless Mesh Networks

    Differential evolution optimization for constrained routing in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Ahmed, Gharib Subhi Mahmoud, Anwar, Farhat, Zakaria, Omar

    Published 2014
    “…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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  6. 6
    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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  7. 7
    Biological-based semi-supervised clustering algorithm to improve gene function prediction

    Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

    Published 2011
    “…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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  8. 8
    Literature Review of Optimization Techniques for Chatter Suppression In Machining

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
    “…Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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  9. 9
    Autonomous and deterministic supervised fuzzy clustering

    Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

    Published 2010
    “…The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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  10. 10
    Document clustering for knowledge discovery using nature-inspired algorithm

    Document clustering for knowledge discovery using nature-inspired algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2014
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  11. 11
    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. …”
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  12. 12
    Balancing exploration and exploitation in ACS algorithms for data clustering

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…The performance of the proposed algorithm is compared with that of several common clustering algorithms using real-world datasets. …”
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  13. 13
    Determining the preprocessing clustering algorithm in radial basis function neural network

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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  14. 14
    Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows

    Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows by Afzal, Asif, Aabid, Abdul, Khan, Ambareen, Khan, Sher Afghan, Rajak, Upendra, Verma, Tikendra Nath, Kumar, Rahul

    Published 2020
    “…Regression of both the pressures using a random forest classification algorithm is carried out. …”
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  15. 15
    An Improved LEACH Algorithm Based On Fuzzy C-Means Algorithm And Distributed Cluster Head Selection Mechanism.

    An Improved LEACH Algorithm Based On Fuzzy C-Means Algorithm And Distributed Cluster Head Selection Mechanism. by Hassan, Ali Abdul Hussian, Othman, Mohd Fairuz Iskandar, Md Shah, Wahidah, Husien, Ali Mohamed, Hassan, Hayder Abdul Hussien

    Published 2019
    “…In LEACH algorithm, the random manner is used to select specific nodes as a cluster heads. …”
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  16. 16
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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  17. 17
    Identifying clusters structure of rare events using random forest clustering

    Identifying clusters structure of rare events using random forest clustering by Zaturrawiah A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, Norhafiza Hamzah

    Published 2021
    “…To identify the intrinsic structures in the minority class (the stroke group), Random Forest Clustering was used to produce the proximity matrix and fed to Partition around Medoid (PAM) clustering method to identify the optimal number of clusters. …”
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  18. 18
    Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification

    Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification by Juma, Sundus, Muda, Zaiton, Yassin, Warusia

    Published 2014
    “…X-Means clustering is utilized to gather whole data into congruent cluster based on their behaviour whereas Random Forest classifier is utilized to rearrange the misclassified clustered data to apropos group. …”
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  19. 19
    Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement

    Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

    Published 2023
    “…In this thesis, the accuracy of the proposed algorithm was evaluated using two standard online benchmarking database systems. …”
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  20. 20
    A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering

    A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering by Prasetyadi, Abdurrakhman, Nugroho, Budi, Tohari, Adrin

    Published 2022
    “…Nevertheless, it is difficult to obtain a homogeneous clustering result of the k-means method because this method is sensitive to a random selection of the centers of the cluster. …”
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