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  1. 1
    Improving intrusion detection using genetic algorithm

    Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

    Published 2013
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  2. 2
    An adaptive anomaly threshold in artificial dendrite cell algorithm

    An adaptive anomaly threshold in artificial dendrite cell algorithm by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

    Published 2017
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  3. 3
    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction

    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

    Published 2024
    “…Therefore, a fuzzy model based on machine learning and data mining is a vital solution. In this study, ten supervised machine learning algorithms namely the J48, Logistic, NaiveBayes Updateable, RandomTree, BayesNet, AdaBoostM1, Random Forest, Multilayer Perceptron, Bagging and Stacking are applied for a simulated diabetes fuzzy dataset, verified by medical experts. …”
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  4. 4
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  5. 5
    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The integrated BayesNet ML-ADR fault classifier model eliminates the under-reach effect compromise on the zone-3 backup protection element for accurate fault detection, classification, and trip decision time reduction during far-end boundary faults. …”
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  6. 6
    Identification of alzheimer diseaseassociated pathways and network using transcriptome analysis / Lau Ching Yee

    Identification of alzheimer diseaseassociated pathways and network using transcriptome analysis / Lau Ching Yee by Lau , Ching Yee

    Published 2018
    “…Since complex diseases like AD can be better understood from the perspective of network biology than at the individual gene level, we used NetDecoder, a state-of-the-art network-based transcriptomic analysis algorithm to capture genes that are associated with the differentially expressed genes in a network context. …”
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  7. 7
    Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman

    Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman by Muhammad Habib , Ur Rehman

    Published 2016
    “…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. Alternately, the platform level complexity increases due to mobility and limited availability of computational and battery power resources in mobile devices, high coupling between application components, and dependency over Internet connections. …”
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  8. 8
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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