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Correlation Clustering via s-Club Cluster Edge Deletion
Published 2023Subjects: “…Cluster analysis -- Data processing…”
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…”
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Parallel implementation of clique partitioning using artificial neural networks. (c2000)
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…The benefits of the proposed algorithms in addressing real-world issues with challenging and unknown search areas are demonstrated by the outcomes of real-world case studies. …”
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…Unfortunately, PCA’s reliability drops when data has nonlinear characteristics as industrial processes. …”
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