Search Results - (( data distributions clustering algorithm ) OR ( _ application based algorithm ))

Refine Results
  1. 1

    A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution by Nokhanji, Nooshin, Mohd Hanapi, Zurina, Subramaniam, Shamala, Mohamed, Mohamad Afendee

    Published 2014
    “…Energy aware distributed clustering (EADC) is one of the cluster-based routing protocols proposed for networks with nonuniform node distribution, which can effectively balance the energy consumption among the nodes. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

    Published 2021
    “…The data distribution issue remains an unsolved clustering problem in data mining, especially in dealing with imbalanced datasets. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    An energy based cluster head selection unequal clustering algorithm with dual sink (ECH-DUAL) for continuous monitoring applications in wireless sensor networks by Alagirisamy, Mukil, Chow, Chee Onn

    Published 2018
    “…In our algorithm, tentative cluster head is selected based on energy based timer, residual energy, node IDs and trust value. …”
    Get full text
    Get full text
    Article
  5. 5

    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

    Published 2025
    “…To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. …”
    Get full text
    Get full text
    Get full text
    Thesis
  6. 6
  7. 7

    Energy efficient geographical and power based clustering algorithm for heterogeneous wireless sensor networks by Jahan, Mohammad Saukat, Sali, Aduwati, Azarbad, Bahman, Usaha, Wipawee, A. Rasid, Mohd Fadlee, Mohd Ali, Borhanuddin

    Published 2011
    “…To solve this problem in this paper, we propose Geographical and power based clustering algorithm (GPCA): a heterogeneous-aware clustering protocol, which has significant impact on the entire energy dissipation of WSNs. …”
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…The proposed algorithm consists of several stages, includes data pre-processing, feature selection, feature extraction, clustering and characteristic interpretation. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  9. 9

    Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

    Published 2023
    “…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks by Alhalabi, Huda A. H.

    Published 2019
    “…A Multi-Hop Selective Constructive Interference Flooding (MSCIF) protocol is proposed to address the problem of low connectivity in WSNs with a sparse distribution and improve the network’s lifetime. MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. …”
    Get full text
    Get full text
    Thesis
  11. 11

    Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model by Sulaiman , Marizan, Adnan, Tawafan, Ibrahim, Zulkifilie

    Published 2013
    “…It is evident from the outcomes that the proposed algorithm can effectively differentiate the HIFs from other events in power distribution feeder.…”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study by Lai, Daphne Teck Ching, Owais A. Malik

    Published 2022
    “…Gower distance was used for measuring similarity for mixed data types. To evaluate the clusters found; cluster distribution and Silhouette index were used for cluster quality, Cohen's Kappa Index for cluster stability and Cramer's V Coefficient for clinical relevance of clusters. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
    “…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System by Tawafan, Adnan, Sulaiman , Marizan, Ibrahim, Zulkifilie

    Published 2012
    “…The results show that the proposed algorithm can distinguish successfully HIFs from other events in distribution power system…”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Clustering of Indonesian forest fires using self organizing maps by Selamat, Ali, Selamat, Md. Hafiz

    Published 2006
    “…This paper focuses on clustering the locations of Indonesian forest fires and visualizing them into a two-dimensional map using a self-organizing map (SOM) algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

    Published 2020
    “…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Temporal - spatial recognizer for multi-label data by Mousa, Aseel

    Published 2018
    “…Hence, there is a need for a recognition algorithm that can separate the overlapping data points in order to recognize the correct pattern. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    A Novel Soft Set Approach in Selecting Clustering Attribute by Qin, Hongwu, Ma, Xiuqin, Jasni, Mohamad Zain, Herawan, Tutut

    Published 2012
    “…Clustering is one of the most useful tasks in data mining process for discovering groups and identifying interesting distributions and patterns in the underlying data. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

    Published 2011
    “…This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. …”
    Get full text
    Get full text
    Article