Search Results - (( developing learning innovation algorithm ) OR ( java data optimization algorithm ))
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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A random search based effective algorithm for pairwise test data generation
Published 2011“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Conference or Workshop Item -
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Scalable approach for mining association rules from structured XML data
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Conference or Workshop Item -
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Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology
Published 2024“…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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EasyA: Easy and effective way to generate pairwise test data
Published 2013“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Thesis -
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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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Do CEO and chairman characteristics affect green innovation? evidence from a comparative analysis of machine learning models
Published 2024“…Using the extreme gradient boosting (XGBoost) algorithm, which is at the forefront of machine learning algorithms, this study comprehensively examines the impact of CEO and chairman characteristics on corporate green innovation. …”
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The impact of virtual reality on programming algorithm courses on student learning outcomes
Published 2024“…The low learning outcomes of students and the limitations of learning media provide opportunities to develop innovations that can increase student engagement. …”
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Smart object detection using deep learning algorithm and jetson nano for blind people
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Strategic capabilities, innovation strategy and the performance of food and beverage small and medium enterprises
Published 2019“…Similarly, top management, technological, learning and relational capabilities significantly and positively related to SMEs innovation strategy. …”
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Thesis -
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Mobile application for sign language learning with real time feedback
Published 2024“…This project proposes developing an innovative mobile application for interactive sign language learning to benefit both Deaf individuals and hearing loss individuals globally. …”
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Final Year Project / Dissertation / Thesis -
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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system
Published 2022“…In this paper, we have examined and presented the most recent research on developing robust IDSs using Deep Learning (DL) algorithms, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Stacked Autoencoders (SAE), and Deep Belief Networks (DBN). …”
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