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  1. 1

    A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…The proposed QGGABC-ANN based on bio-inspired learning algorithm with its high degree of accuracy could be used as an investment advisor for the investors and traders in the future of SSM. …”
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    Article
  2. 2

    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

    Published 2024
    “…Models were trained several times with different configuration (nodes in hidden layers) to achieve better accuracy. The final optimum learning algorithm was selected based on the performance values (regression…”
    Article
  3. 3

    A Multi-Criteria Recommendation Technique for Personalized Tourism Experiences by Mustafa, Payandenick, Yin Chai, Wang

    Published 2025
    “…Using ResNet, the algorithm can learn more complex and nuanced patterns in the data, leading to more accurate recommendations. …”
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    Thesis
  4. 4

    Machine-learning guided fracture density seismic inversion: A new approach in fractured basement characterisation by Shamsuddin, A.A.S., Purnomo, E.W., Ghosh, D.P.

    Published 2020
    “…A machine learning algorithm of well log fracture density - borehole image log (BHI) guided seismic inversion was performed. …”
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    Conference or Workshop Item
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    A machine learning approach to tourism recommendations system by Chia, An

    Published 2025
    “…To overcome this problem, this project implements machine learning algorithms with collaborative filtering, content-based filtering and hybrid filtering approaches. …”
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    Final Year Project / Dissertation / Thesis
  7. 7

    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

    Published 2024
    “…This dataset, alongside key parameters like cover-to-depth ratio, pillar width, soil stiffness, cohesion, friction angle, and overburden-to-face pressure ratio, integrates into a machine learning framework using a theory-guided approach. …”
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    Thesis
  8. 8

    IOT-based fertigation system / Mohamad Amir Furqan Darus by Darus, Mohamad Amir Furqan

    Published 2024
    “…These sensors provide real-time data about the crops’ environment, which is then sent to a central hub or cloud platform. Advanced algorithms and machine learning processes this data to determine the ideal irrigation and fertilization needs. …”
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    Student Project
  9. 9

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

    Published 2011
    “…The simulation results indicate that the algorithm is able to suggest a word, based on the design settings. …”
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    Thesis
  10. 10

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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    Thesis
  11. 11

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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    Thesis
  12. 12

    An augmented sequential MCMC procedure for particle based learning in dynamical systems by Javvad ur Rehman, M., Dass, S.C., Asirvadam, V.S.

    Published 2019
    “…We address the problem of particle-based learning when sufficient statistics and tractable distributions for sampling are not available. …”
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    Article
  13. 13

    The impact of news sentiment on the stock market fluctuation : the case of selected energy sector by Ling, Wu, Siew, Hock Ow

    Published 2021
    “…We developed a financial news sentiment classifier by combining machine learning algorithms and lexicon-based labelling methods. …”
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    Article
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    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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    Thesis
  16. 16

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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    Thesis
  17. 17

    Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2026
    “…A sandbox for readers to learn, skill-build, and develop in, ‘Intelligent Energy Systems using BMO and EMA’ provides an indispensable guide to these cutting-edge AI tools for new and experienced readers.…”
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    Book
  18. 18

    Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

    Published 2020
    “…The eight input vectors used in this study were rock type, WAG process type (miscible, immiscible), reservoir permeability, oil gravity, oil viscosity, reservoir temperature, reservoir pressure, and hydrocarbon pore volume of gas injected. Based on literature review, Random Forest (RF) learning method was selected to predict the WAG incremental recovery factor and rank the input vector based on their importance. …”
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    Article
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    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
    Article