Search Results - (( java application customization algorithm ) OR ( using implementation clustering algorithm ))

Search alternatives:

Refine Results
  1. 1
    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients

    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Consequently, the implementation of z-numbers in fuzzy clustering algorithm is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in uncertain information development. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  2. 2
    Image segmentation based on normalised cuts with clustering algorithm

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

    Published 2013
    “…As the clusters initialisation gives influence to the segmentation result, optimisation of the clustering algorithm is implemented to achieve a better segmentation. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    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. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms

    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms by Raheem, Ajiboye Adeleke, Hauwau, Isah-Kebbe, O., Oladele Tinuke

    Published 2014
    “…Experiments were conducted using k-means, k-medoids and EM-algorithm. The study implements each algorithm using RapidMiner Software and the results generated was validated for correctness in accordance to the concept of external criteria method. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    Clustering for binary data sets by using genetic algorithm-incremental K-means

    Clustering for binary data sets by using genetic algorithm-incremental K-means by Saharan, S., Baragona, R., Nor, M. E., Salleh, R. M., Asrah, N. M.

    Published 2018
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Enhanced Clustering Algorithms For Gray-Scale Image Segmentation

    Enhanced Clustering Algorithms For Gray-Scale Image Segmentation by Siddiqui, Fasahat Ullah

    Published 2012
    “…The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm

    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

    Published 2012
    “…This document is a study about LEACH algorithm where the implementation was done using OMNeT++ network simulator to study the performance of this algorithm in term of network lifetime. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
    “…The proposed algorithm has been implemented on an experimental Beowulf cluster which consists of 12 nodes operating on Linux Ubuntu platform. …”
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  10. 10
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…Information theory based concepts of mean gain ratio and entropy of clusters are used to implement these two steps, respectively. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data

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

    Published 2014
    “…This research proposes mean gain ratio (MGR), a new information theory based hierarchical divisive clustering algorithm for categorical data. MGR implements clustering from the attributes viewpoint which includes selecting a clustering attribute using mean gain ratio and selecting an equivalence class on the clustering attribute using entropy of clusters. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection

    Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli

    Published 2011
    “…One of most used clustering method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques

    A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…First we present an overview of both methods with emphasis on the implementation of the algorithm. Then, we apply six datasets to measure the quality of clustering result based on the similarity measure used in the algorithm and its representation of clustering result. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  14. 14
    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. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds

    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm.…”
    Get full text
    Get full text
    Get full text
    Book Section
    Save to List
    Saved in:
  16. 16
    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering

    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

    Published 2019
    “…As these clustering algorithms require the number of clusters as input parameter of the algorithms, the study of number of clusters for the clustering is served as focus in this paper. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
    Save to List
    Saved in:
  17. 17
    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor

    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor by Abu Mangshor, Nur Nabilah

    Published 2010
    “…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm

    Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm by Nor, N.H.M., Daud, H., Ullah, S.

    Published 2022
    “…Parametric assumptions commonly implemented in most of algorithm in cluster detections. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  19. 19
    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING

    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

    Published 2010
    “…Document clustering is an implementation of data mining task. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: