Search Results - (( based education data algorithm ) OR ( based optimization based algorithm ))

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  1. 1

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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    Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

    Published 2020
    “…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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  4. 4

    Efficient and stable routing algorithm based on user mobility and node density in urban vehicular network by Al-Mayouf, Y.R.B., Ismail, M., Abdullah, N.F., Wahab, A.W.A., Mahdi, O.A., Khan, S., Choo, R.K.K.

    Published 2016
    “…Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). …”
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    Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii by Shafii, Muhammed Khaleeq

    Published 2012
    “…This would give a brief overview on which techniques or algorithms give better optimization and faster results in generating Prediction of UPSR result. …”
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    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

    Published 2024
    “…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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    Automated Student Timetable Scheduling System based on Genetic Algorithm by Amirul Azuani, Romlee, Noor Ain, Rosly, Meng, Chuan Haw

    Published 2019
    “…Genetic algorithm works based on natural evolutions that comprises of several iterations. …”
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    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…As a solution, nature inspired metaheuristic algorithms provide derivative-free solution to optimize complex problems. …”
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    A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation by Rong, Li, Shari, Zalina, Ab Kadir, Mohd Zainal Abidin

    Published 2025
    “…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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    Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making by Chuan, Zun Liang, Japashov, Nursultan, Yuan, Soon Kien, Tan, Wei Qing, Noriszura, Ismail

    Published 2024
    “…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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    Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda by Mohamad @ Hamza, Mohd. Azwan

    Published 2006
    “…MMB Technique only required a small size of training data. (3) Prediction process of writing style using Multiple Linear Regression (MLR) Algorithm. MLR Algorithm applied six fixed features (based on previous research) to ensure the prediction is more standardize and feature set is more significant. (4) Test the performance agreement derived from the combination of MMB, MLR and data of language component (taken from human assessment) and compared it to human assessment for five cycles of cross-validation. …”
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    Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

    Published 2025
    “…Adaptive gradient-based algorithms, including ADAM, NADAM, ADADELTA, ADAGRAD, and ADAMAX, exhibited superior performance. …”
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    Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making by Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae

    Published 2023
    “…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel stacked ensemble machine learning algorithm based on these determinants, following the CRISP-DM data science methodology. …”
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    The exploration of hybrid metaheuristics-based approaches: A bibliometric analysis by Nur Hidayah, Azmidi, Noryanti, Muhammad, Rozieana, Khairuddin

    Published 2025
    “…The study findings indicate a growing and broader trend towards the integration of metaheuristics and optimization algorithms, echoing the interdisciplinary nature of this domain. …”
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