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  1. 1

    Design of artificial intelligence-based electronic Malay language learning tool for visually impaired children by Yeoh, Sing Hsia

    Published 2011
    “…The advancement of technology in twenty-first century should provide more design of great learning devices. …”
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    Thesis
  2. 2

    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 first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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    Thesis
  3. 3

    A review on monocular tracking and mapping: from model-based to data-driven methods by Gadipudi, N., Elamvazuthi, I., Izhar, L.I., Tiwari, L., Hebbalaguppe, R., Lu, C.-K., Doss, A.S.A.

    Published 2022
    “…This paper provides an extensive review of the developments for the first two decades of the twenty-first century. Astounding results from early methods based on filtering have intrigued the community to extend these algorithms using other forms of techniques like bundle adjustment and deep learning. …”
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    Article
  4. 4

    A review on learning taxonomies from Malay text corpora by Ahmad Nazri, Mohd. Zakree, Shamsuddin, Siti Mariyam, Abu Bakar, Azuraliza

    Published 2007
    “…But there are no comparative work systematically analyzing different techniques and algorithms on learning concept hierarchies from a Malay text. …”
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    Article
  5. 5

    DSC722: Research Methodology / College of Computing, Informatics and Mathematics by UiTM, College of Computing, Informatics and Mathematics

    Published 2020
    “…Students will learn innovative ways of harnessing data to transform knowledge and optimize processes in the 21st century.…”
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    Teaching Resource
  6. 6

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…A data summarization approach is proposed due to its capability to learn data stored in multiple tables. In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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    Research Report
  7. 7

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
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    Article
  8. 8

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
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    Article
  9. 9

    Application of phi (Φ), the golden ratio, in computing: a systematic review by Akhtaruzzaman, M, Tanvin, Jamal Uddin, Shafie, Amir Akramin, Shahryer, Fahim, Halder, Sachitra

    Published 2024
    “…The review also categorizes findings by their specific applications and contexts, providing valuable insights into φ’s impact on mathematics, cryptography, search algorithms, machine learning, artificial intelligence, photonics, natural sciences, system design, power engineering, robotics, and practical human life. …”
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    Article
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    Why coding? Why now? From coding to computational thinking through computational mathematics problem based learning (CM-PBL) by Ku, Soh Ting, Talib, Othman, Md. Yunus, Aida Suraya, Zolkepli, Maslina

    Published 2019
    “…Rather than emphasizing student learning passively through listening, watching, practicing exercises and imitating isolated skills, the CM-PBL learning framework allowing students to simulate and build their own computational models to support their self-learning and understanding of mathematic concepts. …”
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    Conference or Workshop Item
  12. 12

    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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    Thesis
  13. 13

    Artificial Intelligence as A Common Heritage of Mankind by Wye, Dennis Keen Khong, Su, Wai Mon

    Published 2023
    “…Artificial intelligence technologies today employ techniques known as machine learning and deep learning, which apply datasets to a suitable mathematical or statistical technique known as an algorithm. …”
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    Article
  14. 14

    Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

    Published 2025
    “…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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    Book Section
  15. 15

    Word problems as a vehicle for teaching computational thinking by Ting, Ku Soh, Talib, Othman, Mohd Ayub, Ahmad Fauzi, Zolkepli, Maslina, Yee, Chen Chuei, Hoong, Teh Chin

    Published 2023
    “…Students can use the CM-PBL learning framework to simulate and build their own computational models as to aid their self-learning and comprehension of mathematical concepts. …”
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    Article
  16. 16

    A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

    Published 2023
    “…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
    Article
  17. 17

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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    Thesis
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    Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2017
    “…The combination of ML algorithms and EW pattern detector achieved significantly higher performance compare to the ML algorithms only.…”
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    Article
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