Search Results - (( java implementation path algorithm ) OR ( using complex clustering algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    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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    Thesis
  3. 3
  4. 4

    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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    Thesis
  5. 5

    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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    Article
  6. 6

    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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    Thesis
  7. 7
  8. 8

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
    “…Time-series clustering is not only useful as an exploratory technique but also as a subroutine in more complex data mining algorithms. …”
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    Thesis
  9. 9

    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data by Hongwu, Qin, Ma, Xiuqin, Herawan, Tutut, Jasni, Mohamad Zain

    Published 2014
    “…While many algorithms for clustering categorical data have been proposed, some have low clustering accuracy while others have high computational complexity. …”
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    Article
  10. 10

    Image segmentation based on normalised cuts with clustering algorithm by Choong, Mei Yeen

    Published 2013
    “…Clustered segments from the local segmentation are then used for image segmentation in global perspective. …”
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    Thesis
  11. 11

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…A genetic algorithm (GA) is also used to find the best centroids for all the clusters generated cluster centroids. …”
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    Thesis
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  13. 13

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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    Thesis
  14. 14

    Clustering Spatial Data Using a Kernel-Based Algorithm by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2005
    “…Therefore, this work comes up with new clustering algorithm using kernel-based methods for effective and efficient data analysis by exploring structures in the data.…”
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    Conference or Workshop Item
  15. 15

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

    Published 2014
    “…This study proposes a density-based algorithm for clustering evolving data streams. The proposed method, which is called MuDi-Stream (Multi Density clustering algorithm for evolving data Stream), is an online-offline algorithm with four main components. …”
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    Thesis
  16. 16

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…The unsupervised solution using time series clustering algorithms is capable to extract valuable information and identify structure in complex and massive datasets as spatial time series. …”
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    Article
  17. 17

    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

    Published 2024
    “…The findings of the experiments are compared to the outcomes of BOCEDS, CEDAS, and MuDi-Stream algorithms. The outcomes indicate that the EWR algorithm outperformed the baseline clustering algorithms. …”
    Article
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    An intelligent categorization tool for malay research articles by Mohd Norhisham Razali, Rayner Alfred, Chin, Kim On

    Published 2015
    “…Hence, by increasing the mapping percentage for the bilingual clusters, a more robust clustering algorithm can be developed for clustering bilingual documents. …”
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    Research Report
  19. 19

    Constrained clustering approach to aid in remodularisation of object-oriented software systems / Chong Chun Yong by Chong, Chun Yong

    Published 2016
    “…Even if maintainers possess additional information that could be useful to guide and improve the clustering results, traditional clustering algorithms have no way to take advantage of this information. …”
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    Thesis
  20. 20

    An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

    Published 2021
    “…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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    Article