Search Results - (( java application optimisation algorithm ) OR ( automatic identification bayes algorithm ))

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  1. 1

    Texture-based feature using multi-blocks gray level co-occurrence matrix for ethnicity identification by Mohd Zamri, Osman, M. A., Maarof, Mohd Foad, Rohani

    Published 2020
    “…Then, final stage was undergone with several classification algorithms such as Naïve Bayes, BayesNet, kNearest Neighbour (k-NN), Random Forest, and Multilayer Perceptron (MLP). …”
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  2. 2

    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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  3. 3

    The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification by Mokhairi, Makhtar, Engku Fadzli Hasan, Syed Abdullah, Fatma Susilawati, Mohamad

    Published 2015
    “…For the classification experiment, it was tested using four types of classifiers: BayesNet, NaiveBayesUpdateable, RandomTree and IBk.…”
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    Article
  4. 4

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  5. 5

    Advancing machine learning for identifying cardiovascular disease via granular computing by Ku Muhammad Naim, Ku Khalif, Noryanti, Muhammad, Mohd Khairul Bazli, Mohd Aziz, Mohammad Isa, Irawan, Mohammad Iqbal, ., Muhammad Nanda, Setiawan

    Published 2024
    “…Machine learning algorithms such as Naïve Bayes, k-nearest neighbor, random forest, and gradient boosting are commonly used in constructing these models. …”
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  6. 6
  7. 7

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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    Thesis