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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
Published 2021“…Optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) algorithm , ant colony algorithm, and many other algorithms are used along with classifiers to improve the work of these classifiers in detecting intrusion and to increase the performance of these classifiers. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Being that feature subset selection is considered a multi-objective optimization problem, this study proposed the Rao-SVM as an FSS mechanism; its algorithm-specific and parameter-less concept was also explored. …”
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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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An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
Published 2011“…The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…In this research, two machine learning models, Deep Neural Network (DNN) and Support Vector Machine (SVM), are utilized for sound classification. Both models' parameters are optimized to achieve optimal performance. …”
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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz
Published 2019“…Therefore, Cuckoo Search Algorithm (CS) is hybrid with LS-SVM in order to optimize the RBF parameters for a better prediction performance. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…As a consequence, HAR has been identified as a potential topic for healthcare assessment systems. One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
Published 2011“…The idea is to use CGA to find the optimal values of regularization parameter, γ and Kernel RBF parameter, σ 2 , and adapt a supervised learning approach to train the LS-SVM model. …”
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Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS
Published 2025“…Then, open-phase localization is achieved using the Support Vector Machine (SVM) with hyperparameter Bayesian Optimization (BO). …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation
Published 2020“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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