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1
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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masterThesis -
2
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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masterThesis -
3
Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
4
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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conferenceObject -
5
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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Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence
Published 2020“…Moreover, majority of improvements made by the researchers in optimization techniques have focused on the accuracy of solution and have overlooked the convergence speed of an algorithm. 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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A three-stage hybrid heuristic algorithm for the capacitated vehicle routing problem. (c2016)
Published 2016“…We propose a three-stage hybrid heuristic approach consisting of a mixture of five algorithms that are run in parallel, differing only in the clustering stage. …”
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masterThesis -
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities
Published 2021“…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…From this, it is observed that the ANN provides effective forecasting results. In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. …”
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The multi-parameterized cluster editing problem
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conferenceObject -
14
(k, l)-Clustering for Transactional Data Streams Anonymization
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conferenceObject -
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Cooperative clustering models for Vehicular ad hoc networks. (c2013)
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masterThesis -
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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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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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Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem
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