Search Results - (( data implementation means algorithm ) OR ( java application learning algorithm ))

Refine Results
  1. 1

    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
  2. 2

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3
  4. 4

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The K-means algorithm requires two inputs for it to be applied onto a data set, the value K, and a proximity measure. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  5. 5
  6. 6

    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
    “…In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.…”
    Get full text
    Get full text
    Article
  7. 7

    Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

    Published 2010
    “…This algorithm implements k-means to initialize the fuzzy model. …”
    Get full text
    Get full text
    Article
  8. 8

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    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
  11. 11

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. Additionally, tests demonstrate that combining canopy and the K-means algorithm to analyze data performs consistently and dependably on the Hadoop platform and has a clustering result that offers a scalable and effective solution for power system monitoring. ? …”
    Article
  12. 12

    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

    Published 2023
    “…The purpose of this study is to apply the K-Means algorithm to perform clustering on COVID-19 data to determine the high spread of the virus in regions in Indonesia based on the frequency of the data. …”
    Get full text
    Get full text
    Book Section
  13. 13

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
    “…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
    Get full text
    Get full text
    Book Section
  15. 15

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
    Get full text
    Get full text
    Article
  16. 16

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
    Get full text
    Get full text
    Article
  17. 17

    Implementation of perez-dumortier calibration algorithm by Jedol Dayou, Chang, Jackson Hian Wui, Justin Sentian

    Published 2014
    “…To avoid the unnecessary needs to travel to high altitude for sunphotometers calibration, Perez-Dumotier calibration algorithm has been used as an objective means to select the right intensity data so that the calibration can be performed at any altitude levels. …”
    Get full text
    Get full text
    Get full text
    Chapter In Book
  18. 18

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20