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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz
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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Dual-tone multifrequency signal detection using support vector machines
Published 2023Subjects:Conference paper -
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Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
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. …”
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Feature extraction and supervised learning for volatile organic compounds gas recognition
Published 2023“…The performance of each model was evaluated and compared using k-Fold cross-validation (k=10) and metrics derived from the confusion matrix. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…Later, a Least-Squares Support Vector Machine (LS-SVM) model was developed using cross-validation technique. …”
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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq
Published 2023“…To overcome these challenges, the current research aims to develop a SpatioTemporal Decision-Making (STDM) model based on Geospatial Artificial Intelligence (GeoAI) to locate onshore wind-solar hybrid plants. …”
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A comparative study of supervised machine learning approaches for slope failure production
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
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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Human hearing disorder recognition model using eeg-aep based signal
Published 2022“…Firstly, fifteen feature extraction methods were used to extract information from the raw AEP features. Then, the extracted feature was classified using machine learning and deep learning algorithms. …”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study
Published 2024“…RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. …”
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Published 2018“…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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Integrating Phq-9 Sentiment Analysis and Clinical Interviews for Depression Detection in Medical Students
Published 2026thesis::master thesis -
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification
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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Time series data intelligent clustering algorithm for landslide displacement prediction
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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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
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