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    Parallel matrix-multiplication algorithm on network of workstations by Md. Aminuddin, Rusdi, Abdullah, Rosni, Hassan, Suhaidi

    Published 2004
    “…However, these types of algorithms often carried out on expensive supercomputers or multiprocessing systems. …”
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    Article
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    Hybrid FFT-ADALINE algorithm with fast estimation of harmonics in power system by Goh, Zai Peng, Mohd Radzi, Mohd Amran, Thien, Yee Von, Hizam, Hashim, Abdul Wahab, Noor Izzri

    Published 2016
    “…The theory of the proposed algorithm is the application of FFT with weights updating rule to reduce the error of ADALINE instantaneously. …”
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    Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

    Published 2025
    “…The application of the recently developed flow direction algorithm, including its multi-objective variant with an �-based constraint-handling mechanism to OPF problem is the primary contributions of this work. …”
    Article
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    DC-based PV-powered home energy system by Sabry, Ahmad H.

    Published 2017
    “…The disposal of the DC-AC inverter opens the horizon toward high efficiency Solar-Battery-Load system not only in the residential applications but also in general.…”
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    Thesis
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    Facial image retrieval on semantic features using adaptive mean genetic algorithm by Shnan, Marwan Ali, Rassem, Taha H., Nor Saradatul Akmar, Zulkifli

    Published 2019
    “…The performance matrix of the AMGA was compared to those of particle swarm optimization algorithm (PSO) and genetic algorithm (GA) and found to perform better; thus, proving its efficiency.…”
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    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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    Conference or Workshop Item