Search Results - (( developing data learning algorithm ) OR ( java visualization _ algorithm ))

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  1. 1

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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    Monograph
  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. …”
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    Conference or Workshop Item
  3. 3

    A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

    Published 2016
    “…The results of the CPU profiler of Java VisualVM showed that Binary-Based algorithm performs better than Eclat algorithm in-terms of both execution times and memory usage. …”
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    Conference or Workshop Item
  4. 4

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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    Conference or Workshop Item
  5. 5

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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    Final Year Project / Dissertation / Thesis
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    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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    Thesis
  8. 8

    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
    “…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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    Article
  9. 9

    Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin by Nasaruddin, Amir Hambaly

    Published 2019
    “…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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    Thesis
  10. 10

    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

    Published 2019
    “…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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    Article
  11. 11

    Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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    Article
  12. 12

    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

    Published 2021
    “…At present, there are many prediction algorithms based on machine learning. According to the "80/20 rule" for building machine learning model, 80% of the time is spent of finding, cleaning, and organizing data, while the remaining 20% for training of the machine learning model. …”
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    Thesis
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    Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

    Published 2021
    “…Prediction of total cases and total deaths are obtained by taking previous 14 days of time series data as the input to the machine learning algorithms developed in this paper. …”
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    Article
  15. 15

    Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

    Published 2021
    “…Prediction of total cases and total deaths are obtained by taking previous 14 days of time series data as the input to the machine learning algorithms developed in this paper. …”
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    Article
  16. 16

    Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

    Published 2006
    “…Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. …”
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    Monograph
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    A machine learning approach to tourism recommendations system by Chia, An

    Published 2025
    “…This project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. …”
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    Final Year Project / Dissertation / Thesis
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    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

    Published 2023
    “…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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    Article
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    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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    Conference or Workshop Item