Search Results - (( intelligence based data algorithm ) OR ( intelligence valid svm algorithm ))

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    Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

    Published 2019
    “…This thesis presents a practical and reliable approach for the prediction of PV power output using an intelligent-based technique namely Cuckoo Search Algorithm - Least Square Support Vector Machine (CS-LSSVM). …”
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    Thesis
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    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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    Article
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    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…The prediction result from testing data was validated based on statistical analysis. …”
    Conference Paper
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    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…The reconstruction results are compared with the multi-core CPU and Graphical Processing Unit (GPU) based reconstructions of SENSE. This research also proposed an intelligent and robust classification technique to classify the MRI scans as normal or abnormal and also for validation purpose. …”
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    Thesis
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    Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

    Published 2023
    “…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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    Thesis
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    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification by Saw, Yee Ching

    Published 2018
    “…Paired t-test also carry out to further validated the quality of the FEFR based on the classification accuracy performance metric. …”
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    Thesis
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    Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

    Published 2023
    “…A SVM classifier is trained using the estimated fundamental DTMF carrier frequencies, and is validated using the input samples for classification of low and high DTMF frequency groups. …”
    Conference paper
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    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…During the DD2019 experiment, the RF and SVM algorithms demonstrated the highest levels of accuracy, achieving 96.65% and 93.93%, respectively. …”
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    Article
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    Real-time human activity recognition using external and internal spatial features by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

    Published 2010
    “…Activities are classified by a support vector machine (SVM) with a radial basis kernel. Optimal parameters for the SVM are found through a 10-fold cross-validation. …”
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    Proceeding Paper
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    Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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    Article
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    Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines by Nagi J., Yap K.S., Tiong S.K., Ahmed S.K., Nagi F.

    Published 2023
    “…Key innovations include the use of a Finite Impulse Response (FIR) bandpass filter for reduction of noise from DTMF input samples, and Support Vector Machines (SVM) for intelligent classification of the detected DTMF carrier frequencies. …”
    Conference paper