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  1. 1
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
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  2. 2
    Parallel backpropagation neural network training for face recognition

    Parallel backpropagation neural network training for face recognition by Omarov B., Suliman A., Tsoy A.

    Published 2023
    “…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”
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  3. 3
    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery

    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

    Published 2023
    “…Composed of three levels of learning, the proposed ensemble model employs two base learners and a meta-learner, and is executed in parallel processing platform to achieve efficient computation. …”
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  4. 4
    Fast and efficient sequential learning algorithms using direct-link RBF networks

    Fast and efficient sequential learning algorithms using direct-link RBF networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George

    Published 2003
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  5. 5
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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  6. 6
    Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem

    Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem by Sulaiman M.A.H.B., Suliman A., Ahmad A.R.

    Published 2023
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  7. 7
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  8. 8
    Leveraging data lake architecture for predicting academic student performance

    Leveraging data lake architecture for predicting academic student performance by Abdul Rahim, Shameen Aina, Sidi, Fatimah, Affendey, Lilly Suriani, Ishak, Iskandar, Nurlankyzy, Appak Yessirkep

    Published 2024
    “…With its parallel processing capabilities, this centralized data repository facilitates the training and evaluation of various machine learning models for prediction. …”
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  9. 9
    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living

    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

    Published 2024
    “…Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. …”
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  10. 10
    A review on security and privacy issues in E-learning and the MapReduce aproach

    A review on security and privacy issues in E-learning and the MapReduce aproach by Noor Akma, Abu Bakar, Mazlina, Abdul Majid, Khalid, Adam, Kirahman, Ab Razak, Noorhuzaimi@Karimah, Mohd Noor

    Published 2019
    “…Then, we proposed e-Learning using MapReduce algorithm in protecting the security and privacy of eLearning. …”
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  11. 11
    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
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  12. 12
    A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora

    A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora by Ng Zhen Wei, Chan Chen Jie, Rayner Alfred, Joe Henry Obit

    Published 2012
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  13. 13
    Combining deep and handcrafted image features for MRI brain scan classification

    Combining deep and handcrafted image features for MRI brain scan classification by Hasan, Ali M., Jalab, Hamid A., Meziane, Farid, Kahtan, Hasan, Al-Ahmad, Ahmad Salah

    Published 2019
    “…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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  14. 14
    Small-scale helicopter system identification model using recurrent neural networks

    Small-scale helicopter system identification model using recurrent neural networks by Taha, Z., Deboucha, A., Dahari, M.

    Published 2010
    “…The identification process is conducted by using the well known Levenberg-Marquardt learning algorithm. …”
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  15. 15
    Prognosis of early cervical carcinoma using gene expression profiling

    Prognosis of early cervical carcinoma using gene expression profiling by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…Our results indicate that gene expression profiles combined with carefully chosen learning algorithms can predict patient survival for certain diseases.…”
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  16. 16
    Simulation of Orthogonal Frequency Division Multiplexing (OFDM) signaling

    Simulation of Orthogonal Frequency Division Multiplexing (OFDM) signaling by Mastura, Ibrahim

    Published 2008
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  17. 17
    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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  18. 18
    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy

    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  19. 19
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  20. 20
    Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia

    Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia by Adli Zakaria M.N., Ahmed A.N., Abdul Malek M., Birima A.H., Hayet Khan M.M., Sherif M., Elshafie A.

    Published 2024
    “…Even though the lowest reported performance was reported by the XGBoost, it is the faster of the three algorithms due to its advanced parallel processing capabilities and distributed computing architecture. …”
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