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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Impact learning: A learning method from feature's impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Impact learning: A learning method from feature’s impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, the computational and memory cost of the machine learning is mainly affected by the size of the used datasets. …”
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Performances of machine learning algorithms for binary classification of network anomaly detection system
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
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Underwater Image Recognition using Machine Learning
Published 2024“…Machine Learning is the branch of Artificial Intelligence in which a computer is fed with data and based on that data it tries to find out solution on its own. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Subjects:Conference Paper -
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Machine learning algorithms for early predicting dropout student online learning
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…Moreover, generated topological networks cannot represent the distribution of data. In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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