Search Results - (( java implication based algorithm ) OR ( strategy segmentation clustering algorithm ))

  • Showing 1 - 12 results of 12
Refine Results
  1. 1

    Customer segmentation on clustering algorithms by Toh, Wei Xuan

    Published 2023
    “…Then, k-means, DBSCAN, and GMM clustering algorithms are applied to segment customers based on their buying behaviour. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  2. 2

    Customer segmentation using clustering techniques / Mohamad Amir Salihin Mustafa by Mustafa, Mohamad Amir Salihin

    Published 2024
    “…This study explores clustering techniques for customer segmentation, focusing on the K-Means algorithm in particular, and uses a dataset that was obtained from the customer data of an international supermarket company. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri by Nik Mohd Asri, Nik Asyraniasna

    Published 2024
    “…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
    Get full text
    Get full text
    Thesis
  4. 4

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…Surface defect segmentation algorithms in Automatic Optical Inspection (AOI) system for modern manufacturing industries provide solutions to quality control with speed, volume and traceability. …”
    Get full text
    Get full text
    Thesis
  5. 5

    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

    Published 2021
    “…A profound algorithm comprising of preprocessing in CIELAB color space and Delaunay triangulation based clustering along with Particle Swarm Optimization (PSO) is proposed for the segmentation. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    KopiCulture: Unveiling Customer Loyalty in Malaysia's Coffee Market through Clustering Algorithms for Local Cafe Insights by Tuan Norhafizah, Tuan Zakaria, Che Ku Nuraini, Che Ku Mohd

    Published 2024
    “…This study aims to identify customer loyalty patterns in the Malaysian coffee market, focusing on the Malaysia Starbucks customer survey dataset. Using clustering algorithms such as KMeans, KMeans with Principal Component Analysis (PCA), single linkage, complete linkage, DBScan, and DBScan in conjunction with PCA, we identify distinct customer segments based on loyalty patterns. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

    Published 2016
    “…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. The methods have been applied for detecting, clustering and classification polycrystalline solar wafer images, corresponding to defects such as micro cracks, stain, and fingerprints. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

    Published 2024
    “…In industrial inspection, segmentation algorithms detect product defects, cracks, or anomalies for quality control and safety. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
    Get full text
    Get full text
    Thesis
  11. 11
  12. 12