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  1. 1
    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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  2. 2
    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping by Ahmed Asal Kzar, Ahmed Asal Kzar, M Jafri, Mohd Zubir, Mutter, Kussay N., Anwar, Saumi Syahreza

    Published 2016
    “…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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  3. 3
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  4. 4
    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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  5. 5
    Random sampling method of large-scale graph data classification

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. To address this issue, we propose a novel approximate random sampling method for large-scale graph data classification. …”
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  6. 6
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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    Thesis
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  7. 7
    Adaptive resource allocation for reliable performance in heterogeneous distributed systems.

    Adaptive resource allocation for reliable performance in heterogeneous distributed systems. by Hussin, Masnida, Abdullah, Azizol, K. Subramaniam, Shamala

    Published 2013
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  8. 8
    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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  9. 9
    Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line

    Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

    Published 2020
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  10. 10
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, Norshuhani, Oxley, Alan, Abu Bakar, Zainab

    Published 2012
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  11. 11
    Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor

    Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

    Published 2017
    “…Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. …”
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