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Integrated ACOR/IACOMV-R-SVM Algorithm
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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Conference or Workshop Item -
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An algorithm for Elliott Waves pattern detection
Published 2018“…Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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An algorithm for Elliott Waves pattern detection
Published 2018“…Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…The EFDT and hybrid DT-SVM algorithms were designed and deployed based on DT and SVM algorithms to achieve improved performance. …”
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Solving SVM model selection problem using ACOR and IACOR
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An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
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Conference or Workshop Item -
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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Design and implementation of cordic algorithm with sinusoidal pulse width modulation switching strategy
Published 2017“…Usually, one sinusoidal wave is used for one inverter. In this design, SPWM is used for multilevel inverter application in photovoltaic (PV) system. …”
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Student Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Final Year Project -
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VEHICLE CLASSIFICATION FROM CCTV IMAGES AND VIDEOS
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Final Year Project -
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Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim
Published 2024“…The research contributes a comprehensive exploration of sentiment analysis, combining technical expertise with societal insights. The SVM-based sentiment analyzer offers a user-friendly tool bridging complex algorithms and practical applications. …”
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