Search Results - parallel application ((learning algorithm) OR (means algorithm))

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    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
    “…New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. …”
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    Fast and efficient sequential learning algorithms using direct-link RBF networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George

    Published 2003
    “…The resulting sequential learning approach enables weights to be updated in an efficient parallel manner and facilitates a minimal update extension for real-time applications. …”
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    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    “…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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    Grid portal technology for web based education of parallel computing courses, applications and researches by Alias, Norma, Islam, Md. Rajibul, Mydin, Suhaimi, Hamzah, Norhafiza, Safiza Abd. Ghaffar, Zarith, Satam, Noriza, Darwis, Roziha

    Published 2009
    “…This paper proposes the web service education technology for postgraduate parallel computing course, e-learning students, real-time solutions and for supervising projects related to the application of parallel computing, that focuses on the fundamental principles to parallel computer architecture, multimedia, communication cost, master-worker model, parallel algorithm, web services and performance evaluations. …”
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    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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    A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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    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
    “…Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
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    Wavelet network based online sequential extreme learning machine for dynamic system modeling by Mohammed Salih, Dhiadeen, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil

    Published 2013
    “…Wavelet network (WN) has been introduced in many applications of dynamic systems modeling with different learning algorithms. …”
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    One-dimensional finite element discretization of crack propagation through parallel computation by Islam, Md. Rajibul, Alias, Norma

    Published 2010
    “…We have implemented one dimensional finite element discretization to solve crack propagation problem. The parallel algorithm with parallel computer system has been used in order to perform the computational analysis of finite element for this study. …”
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    Effective software fault localization based on complex network theory / Abubakar Zakari by Abubakar , Zakari

    Published 2019
    “…This has led researchers to adopt approaches such as one bug-at-a-time debugging approach (OBA) and parallel debugging approach. However, using OBA debugging approach increases software time-to-delivery and potentially leads to more faults during regression testing, while utilizing k-mean clustering algorithm with Euclidean distance metric to group failed tests based on their execution profile similarity in parallel debugging approach is claimed to be problematic and inappropriate. …”
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    Thesis