Search Results - (( developing learning clustering algorithm ) OR ( java implementation modified algorithm ))

Refine Results
  1. 1

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

    Published 2006
    “…Whereas kernel-based clustering algorithm is developed for finding clusters in climate data. …”
    Get full text
    Get full text
    Article
  4. 4

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
    Get full text
    Get full text
    Thesis
  5. 5

    Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

    Published 2019
    “…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
    Get full text
    Get full text
    Article
  6. 6

    Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…By gleaning insights from the data, the fuzzy clustering can learn from data, identify patterns and make decisions with minimal human intervention. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Software module clustering based on the fuzzy adaptive teaching learning based optimization algorithm by Kamal Z., Zamli, Fakhrud, Din, Nazirah, Ramli, Ahmed, Bestoun S.

    Published 2019
    “…This paper describes the adoption of Fuzzy Adaptive Fuzzy Teaching Learning based Optimization (ATLBO) for software module clustering problem. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

    Published 2022
    “…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  9. 9

    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
  10. 10

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
    Review
  11. 11

    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  12. 12

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

    Published 2012
    “…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
    Get full text
    Get full text
    Thesis
  13. 13

    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
    “…Thus, there are two objectives of this paper; (i) to propose a reliable fuzzy clustering algorithm using z-numbers and; (ii) to cluster the Chronic Kidney Disease (CKD) patients based on the selected indicators to identify which cluster the patients belongs to (Cluster 0, Cluster 1, Cluster 2, Cluster 3 or Cluster 4) based on the membership functions defined. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14
  15. 15

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
    Get full text
    Get full text
    Thesis
  16. 16

    K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning by Othman, E.S., Faye, I., Babiker, A., Hussaan, A.M.

    Published 2021
    “…This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. The developed algorithm in this paper had been tested on features from ten students who experienced mathematics learning in a classroom. …”
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    Modified spectral clustering algorithm for semisupervised face annotation modeling by Sheng, Gao You

    Published 2025
    “…Objectives included enhancing LPA accuracy, developing robust constraintbased clustering, and evaluating performance. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

    Published 2013
    “…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
    Get full text
    Get full text
    Thesis
  19. 19

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…This study aims to identify telecom customer segments by utilizing machine learning and subsequently develop a web-based dashboard. …”
    Get full text
    Get full text
    Article
  20. 20

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
    Get full text
    Get full text
    Article