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  1. 1
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  2. 2
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
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  3. 3
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  4. 4
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  5. 5
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  6. 6
    Classification of left/right hand movement from EEG signal by intelligent algorithms

    Classification of left/right hand movement from EEG signal by intelligent algorithms by Baig, M.Z., Javed, E., Ayaz, Y., Afzal, W., Gillani, S.O., Naveed, M., Jamil, M.

    Published 2015
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  7. 7
    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob

    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…This research proposes an intelligent technique for grading agarwood essential oil based on its chemical properties using the artificial neural network (ANN) technique. …”
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  8. 8
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
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  9. 9
    Face recognition-based real-time system for surveillance

    Face recognition-based real-time system for surveillance by Mahdi, F.P., Habib, M.M., Ahad, M.A.R., McKeever, S., Moslehuddin, A.S.M., Vasant, P.

    Published 2017
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  10. 10
    EEG Spectrogram Classification Employing ANN for IQ Application

    EEG Spectrogram Classification Employing ANN for IQ Application by Mahfuzah, Mustafa, Mohd Nasir, Taib, Sahrim, Lias, Zunairah, Murat, Norizam, Sulaiman

    Published 2013
    “…Then, Principal Component Analysis (PCA) is used to reduce the big matrix, and is followed with the classification of the EEG spectrogram image in IQ application using ANN algorithm. …”
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  11. 11
    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme

    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme by Ashour, Mohammed Waleed, Khalid, Fatimah, Al-Obaydee, Mohammed

    Published 2013
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  12. 12
    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning

    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning by Mohammed, Badiea Abdulkarem, Senan, Ebrahim Mohammed, Al-Mekhlafi, Zeyad Ghaleb, Rassem, Taha Hussein, Makbol, Nasrin M., Alanazi, Adwan Alownie, Almurayziq, Tariq S., Ghaleb, Fuad A., Sallam, Amer A.

    Published 2022
    “…The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. …”
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  13. 13
    Classification of EEG Spectrogram Using ANN for IQ Application

    Classification of EEG Spectrogram Using ANN for IQ Application by Mahfuzah, Mustafa, Norizam, Sulaiman

    Published 2013
    “…This texture feature produced big matrix data, thus Principal Component Analysis (PCA) is used to reduce the big matrix. Then, ANN algorithm is employed to classify the EEG spectrogram image in IQ application. …”
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  14. 14
    Customer mobile behavioral segmentation and analysis in telecom using machine learning

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
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  15. 15
    Semantic focus fusion based on deep learning for deblurring effect

    Semantic focus fusion based on deep learning for deblurring effect by Ismail, .

    Published 2024
    “…Due to the limited depth of field (DOF) of camera lens, the camera cannot generate high-quality images without blurred region images. In a rapid development of intelligent computation, such as deep learning algorithm, multi-focus image fusion methods indirectly being involved, such as CNN and PCA Net architectures. …”
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  16. 16
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…This thesis aimed to investigate and develop a novel parameterized architecture design for SENSE algorithm. …”
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  17. 17
    Performance Evaluation of BPSO & PCA as Feature Reduction Techniques for Bearing Fault Diagnosis

    Performance Evaluation of BPSO & PCA as Feature Reduction Techniques for Bearing Fault Diagnosis by Faysal, Atik, Ngui, Wai Keng, M. H., Lim

    Published 2022
    “…The reduced feature subsets were 12 and 35 for PCA and BPSO, respectively. K-Nearest Neighbours (K-NN) was used as an intelligent method for fault diagnosis. …”
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  18. 18
    IMPLEMENTATION OF ADVANCED PROCESS CONTROL FOR FLOW CONTROL APPLICATION

    IMPLEMENTATION OF ADVANCED PROCESS CONTROL FOR FLOW CONTROL APPLICATION by ROSLI, NURFATIHAH SYALWIAH

    Published 2013
    “…Therefore this work also will illustrate the performance of MPC in terms of its stability and handling robustness compared to the conventional PID Controller. A general MPC control algorithm is developed using MATLAB/Simulink Toolboxes. …”
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  19. 19
    Performance evaluation of BPSO & PCA as feature reduction techniques for bearing fault diagnosis

    Performance evaluation of BPSO & PCA as feature reduction techniques for bearing fault diagnosis by Faysal, Atik, Ngui, Wai Keng, Lim, M. H.

    Published 2021
    “…The reduced feature subsets were 12 and 35 for PCA and BPSO, respectively. K-Nearest Neighbours (K-NN) was used as an intelligent method for fault diagnosis. …”
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    Book Chapter
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  20. 20
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…A heuristic algorithm was introduced to generate the initial population for intelligence based genetic algorithm. …”
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