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  1. 1
    Learning style analysis based on Felder-Silverman Index Model using Rule Base algorithm

    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
    “…This process benefits students and strengthens the relationship between educators and students, ensuring a more individual or personal approach to learning. The system is developed using the PHP and CSS programming languages, with XAMPP and MySQL serving as the database that stores the necessary information. …”
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  2. 2
    BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning

    BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

    Published 2023
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  3. 3
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    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
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    Research Reports
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  4. 4
    Genetic Algorithm for vehicle routing problem / W.Nurfahizul Ifwah W.Alias, Mohd Shaiful Sharipudin and Shamsunarnie Mohamed Zukri.

    Genetic Algorithm for vehicle routing problem / W.Nurfahizul Ifwah W.Alias, Mohd Shaiful Sharipudin and Shamsunarnie Mohamed Zukri. by W.Alias, W.Nurfahizul Ifwah, Sharipudin, Mohd Shaiful, Mohamed Zukri, Shamsunarnie

    Published 2012
    “…They are also robust and effective algorithms that are computationally simple and easy to implement.…”
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    Research Reports
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  5. 5
    Sedentary sitting posture recognition with YOLOv3 algorithm / Muhammad Amin Mohamad Razali

    Sedentary sitting posture recognition with YOLOv3 algorithm / Muhammad Amin Mohamad Razali by Mohamad Razali, Muhammad Amin

    Published 2023
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    Thesis
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  6. 6
    General timetabling system for school

    General timetabling system for school by Liew, Sau Poh

    Published 2005
    “…The system is implemented using a heuristic generic algorithm that best fit to the timetabling solution. …”
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    Final Year Project Report / IMRAD
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  7. 7
    Innovative smart phone learning system for graphical systems within covid-19 pandemic

    Innovative smart phone learning system for graphical systems within covid-19 pandemic by Tawafak R.M., Alfarsi G., Jabbar J.

    Published 2023
    “…This paper used the Technology Acceptance Model (TAM) as an m-learning model, and Bresenham�s line algorithm is a calculation system implemented by applications. …”
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  8. 8
    BioGenTool: A Generic Bio-inspired Neural Tool.

    BioGenTool: A Generic Bio-inspired Neural Tool. by Gan Kim Soon, Chang Sim Vui, Chin Kim On, Patricia Anthony

    Published 2018
    “…This tool is developed specifically for researchers with non-computing background who wishes to design an ANN based-solution to a particular numerical problem.…”
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  9. 9
    Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School

    Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

    Published 2021
    “…Computational thinking (CT) is one of the cognitive processes involved in STEM learning which human use in problem-solving to provide computational solutions that humans and machines can support. …”
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  10. 10
    AI chatbot system for educational institutions

    AI chatbot system for educational institutions by Tan, Hui Hui

    Published 2023
    “…This project presents the design and development of an advanced chatbot system powered by deep learning algorithms for intent classification. …”
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    Final Year Project / Dissertation / Thesis
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  11. 11
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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  12. 12
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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  13. 13
    A modified generalized RBF model with EM-based learning algorithm for medical applications

    A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

    Published 2006
    “…An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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    Proceeding Paper
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  14. 14
    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…Nonetheless, OBL-based solutions often consider one particular direction of the opposition. …”
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  15. 15
    Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines

    Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

    Published 2019
    “…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO 2 internal corrosion rate. …”
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  16. 16
    Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines

    Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

    Published 2019
    “…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO2 internal corrosion rate. …”
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  17. 17
    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

    Published 2024
    “…It was shown that our proposed model exhibits stronger search ability compared to other metaheuristic algorithms and Exhaustive Search. Our model enhanced the efficiency of the learning phase, resulting in the number of global solutions accounting for 100 %, and significantly improved the global solution diversity. …”
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  18. 18
    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…Using these C values would make those non-selected Q values more competitive in order to achieve updated and more reliable values. The CDRQ Routing Algorithm provides a solution to the problem addressed above by integrating the advantages of CQ Routing Algorithm and Dual Reinforcement Learning. …”
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  19. 19
    Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications

    Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

    Published 2020
    “…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
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    Conference or Workshop Item
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  20. 20
    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network

    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

    Published 2010
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