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  1. 1

    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
  2. 2

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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    Final Year Project / Dissertation / Thesis
  3. 3

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
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    Conference or Workshop Item
  4. 4

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…An Intelligent Learning System for the turning process was developed. …”
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    Thesis
  5. 5

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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    Thesis
  6. 6

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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    Final Year Project / Dissertation / Thesis
  7. 7

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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    Conference or Workshop Item
  8. 8

    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…The weight of each value in hidden layers will be considered during the learning process. LM algorithm is used to minimize the error during training and testing process. …”
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    Thesis
  9. 9

    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. This study can be helpful in analysing the capabilities of machine learning methodologies for time-series data-sets as well as helping governments in the decision making process for mitigation of the pandemic. …”
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    Article
  10. 10

    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. This study can be helpful in analysing the capabilities of machine learning methodologies for time-series data-sets as well as helping governments in the decision making process for mitigation of the pandemic. …”
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    Article
  11. 11
  12. 12

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

    Published 2020
    “…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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    Thesis
  13. 13

    A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

    Published 2023
    “…This paper examines the progress of researches that exploit multi-agent systems for detecting learning styles and adapting educational processes in e-Learning systems. …”
    Conference Paper
  14. 14

    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
  15. 15

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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    Final Year Project
  16. 16

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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    Article
  17. 17

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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    Article
  18. 18

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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    Article
  19. 19

    Learning style analysis based on Felder-Silverman Index Model using Rule Base algorithm by Nurhakim, Muhammad, Ismail, Suhaila, Mohd Yusop, Nurhafizah Moziyana, Ahmad, Siti Rohaidah

    Published 2024
    “…To overcome this concern, the Learning Style Analysis System (SAGP) was developed to identify and provide recommendations based on individual learning styles. …”
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    Article
  20. 20

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…By implementing soft computing techniques in data mining especially in HR field can enhance the knowledge discovery process for intelligent decision system. Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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    Research Reports