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  1. 1
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
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  2. 2
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  3. 3
    A De-noising Scheme for Wavelet Based Power Quality Disturbances Detection and Classification system

    A De-noising Scheme for Wavelet Based Power Quality Disturbances Detection and Classification system by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2011
    “…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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  4. 4
    A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method

    A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2011
    “…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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    Conference or Workshop Item
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  5. 5
    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Simulation produces satisfactory result in identifying the disturbance and proves that it is possible to use this model for power disturbance classification even in a noisy environment. …”
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  6. 6
    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
    “…These advancements contributed to the efficiency of the model in convergence, rendering it applicable to a wide range of nonlinear classification and prediction problems.…”
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  7. 7
    Topic modelling analysis of depression therapy text: a preliminary study / Teh Faradilla Abdul Rahman ... [et al.]

    Topic modelling analysis of depression therapy text: a preliminary study / Teh Faradilla Abdul Rahman ... [et al.] by Abdul Rahman, Teh Faradilla, Mohd Said, Raudzatul Fathiyah, Buja, Alya Geogiana, Mat Nayan, Norshita

    Published 2024
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  8. 8
    A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee

    A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

    Published 2023
    “…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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