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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…Three datasets - Wholesale dataset, Banknotes dataset, and Iris dataset are used to compare multiple distributed clustering algorithms on different matrices: runtime execution, stability, and accuracy. …”
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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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Correlation Clustering via s-Club Cluster Edge Deletion
Published 2023“…We run these algorithms and cross-compare the three experiment results to the fastest Cluster Editing algorithm which runs in O(1.62k) time. …”
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5
Three-phase simulated annealing algorithms for exam scheduling
Published 2003“…Hence, we refer to our solution methods as 3-phase simulated annealing (3PSA). We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. …”
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Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence
Published 2020“…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …”
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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation
Published 2023“…We found researchers employing 46 different algorithms and 14 different evaluation metrics. For the algorithms, K-means clustering is the most employed. …”
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(k, l)-Clustering for Transactional Data Streams Anonymization
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
Published 2006“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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Stochastic Search Algorithms for Exam Scheduling
Published 2007“…Then, we empirically compare the three proposed algorithms and FESP using realistic data. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
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Particle swarm optimization algorithm: review and applications
Published 2024“…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”
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A genetic algorithm for testable data path synthesis
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