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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2020“…The results of the conducted experiments indicate that random forest outperforms other algorithms achieving a maximum accuracy of 98.5% and an F-score of 0.932. …”
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2019Get full text
doctoralThesis -
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…Given a graph G = (V, E), a clique is a complete subgraph in G. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…The paper uses naive Bayes, Support Vector Machine (SVM), and Random Forest (RF) as classifiers after careful investigation. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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Developing a UAE-Based Disputes Prediction Model using Machine Learning
Published 2022Get full text
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Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Published 2021Get full text
doctoralThesis -
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A hybrid approach for XML similarity
Published 2007“…Owing to an unparalleled increasing use of the XML standard, developing efficient techniques for comparing XML-based documents becomes essential in information retrieval (IR) research. Various algorithms for comparing hierarchically structured data, e.g. …”
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AI-based remaining useful life prediction and modelling of seawater desalination membranes
Published 2024Get full text
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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
Published 2024“…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
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LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”
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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…We employed an ML method based on Random Forest (RF), Logistic Regression (LR), k-Nearest Neighbors (kNN), and Naive Bayes (NB) with a One-versus-Rest (OvR) strategy and then compared our work to other related works. …”