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  1. 1
    Performance of hybrid GANN in comparison with other standalone models on dengue outbreak prediction

    Performance of hybrid GANN in comparison with other standalone models on dengue outbreak prediction by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaacob, Razali, Hamdan, Hazlina, Hussin, Masnida

    Published 2016
    “…The result showed that neighboring location of dengue cases was very effective in predicting the dengue outbreak and it is proven that the hybrid Genetic Algorithm and Neural Network (GANN) model significantly outperforms standalone models namely regression and Neural Network (NN).…”
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  2. 2
    Examining the potential of machine learning for predicting academic achievement: A systematic review

    Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

    Published 2023
    “…The capability to forecast student performance empowers universities to devise an intervention strategy either at the beginning of a program or during a semester, which allows them to tackle any issues that may arise proactively. …”
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  3. 3
    Examining the potential of machine learning for predicting academic achievement: A systematic review

    Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

    Published 2023
    “…The capability to forecast student performance empowers universities to devise an intervention strategy either at the beginning of a program or during a semester, which allows them to tackle any issues that may arise proactively. …”
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  4. 4
    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques

    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

    Published 2021
    “…Topographic information such as feature maps and digital terrain models (DTM) has always been a basic requirement in many engineering sciences. …”
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  5. 5
    Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining

    Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

    Published 2023
    “…It proceeds through three phases of Need Analysis, Development of the Model and Evaluation of the Model. Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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  6. 6
    Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.]

    Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

    Published 2022
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  7. 7
    Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education

    Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education by Muhammad Noorazizi Abd Ghani, Istas Fahrurrazi Nusyirwan

    Published 2025
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  8. 8
    Flexible role transition management in scripting language / Zainura Idrus

    Flexible role transition management in scripting language / Zainura Idrus by Idrus, Zainura

    Published 2015
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  9. 9
    Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad

    Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

    Published 2022
    “…Overall, deep learning using the Tensorflow.Keras (tf.keras) application programming interface (API) makes the development of the DCNN model easier. …”
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